diff --git a/.buildinfo b/.buildinfo
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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 1b90b7a87d83483e91aa630c474b09cf
+tags: 645f666f9bcd5a90fca523b33c5a78b7
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diff --git a/_sources/algorithms.rst.txt b/_sources/algorithms.rst.txt
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+++ b/_sources/algorithms.rst.txt
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+Algorithms
+====================================
+
+
+Grover search
+-----------------
diff --git a/_sources/api.rst.txt b/_sources/api.rst.txt
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+++ b/_sources/api.rst.txt
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+API
+===
+
+.. autosummary::
+   :toctree: generated
+   :recursive:
+
+   qlasskit.qlassfun.qlassf
+   qlasskit.qlassfun.qlassfa
+   qlasskit.qlassfun.QlassF 
+   qlasskit.algorithms.qalgorithm
+   qlasskit.algorithms.grover.Grover
+   qlasskit.qcircuit.qcircuit.QCircuit
+   qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper
+   qlasskit.qcircuit.gates
\ No newline at end of file
diff --git a/_sources/example_grover.ipynb.txt b/_sources/example_grover.ipynb.txt
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Grover search\n",
+    "\n",
+    "We define a function named `and_all` that returns `True` iff all the element of an input list `a_list` are `True`. We want to use a Grover search to find the input value that led to a `True` result of the function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit import qlassf, Qlist, Qint2\n",
+    "\n",
+    "@qlassf\n",
+    "def and_all(a_list: Qlist[bool, 4]) -> bool:\n",
+    "    r = True\n",
+    "    for i in a_list:\n",
+    "        r = r and i\n",
+    "    return r           "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The qlasskit compiler will produce an optimized quantum circuit performing the given function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 203.885x451.5 with 1 Axes>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "and_all.export('qiskit').draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We now can use our quantum function as an oracle for a Grover search. For instance, we want to find the input value that yeld to a `True` value of the function:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit.algorithms import Grover\n",
+    "\n",
+    "q_algo = Grover(and_all, True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Qlasskit prepares the quantum circuit for the Grover search:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2210.55x1120.39 with 1 Axes>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc = q_algo.export('qiskit')\n",
+    "qc.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can use our prefered framework and simulator for sampling the result; this is an example using `qiskit` with `aer_simulator`.\n",
+    "\n",
+    "The `Grover` class, along with all circuit wrappers in qlasskit, provides utilities to encode inputs and decode outputs from a quantum circuit using the high level type definition. In the output histogram, it's now evident that the input leading to a `True` result in the `and_all` function is a list where all elements are set to `True`, aligning with our expectations.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit import Aer, QuantumCircuit, transpile\n",
+    "from qiskit.visualization import plot_histogram\n",
+    "\n",
+    "qc.measure_all()\n",
+    "simulator = Aer.get_backend(\"aer_simulator\")\n",
+    "circ = transpile(qc, simulator)\n",
+    "result = simulator.run(circ).result()\n",
+    "counts = result.get_counts(circ)\n",
+    "\n",
+    "counts_readable = q_algo.decode_counts(counts)\n",
+    "plot_histogram(counts_readable)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "qlasskit_310-env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/_sources/example_grover_hash.ipynb.txt b/_sources/example_grover_hash.ipynb.txt
new file mode 100644
index 00000000..d7ccf386
--- /dev/null
+++ b/_sources/example_grover_hash.ipynb.txt
@@ -0,0 +1,164 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Grover search: hash function preimage attack\n",
+    "\n",
+    "In the ever-evolving landscape of cybersecurity, the advent of quantum computing presents both an extraordinary opportunity and an unprecedented challenge. In this notebook we exploit a Grover Search to perform a preimage attack on a toy hash function.\n",
+    "\n",
+    "A preimage attack on a cryptographic hash function `h(m)` tries to find a message `m` that has a specific hash value. Using qlasskit it is easy to write an hash function like the following `hash_simp`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit import qlassf, Qint4, Qint8, Qlist\n",
+    "\n",
+    "@qlassf\n",
+    "def hash_simp(m: Qlist[Qint4, 2]) -> Qint8:\n",
+    "    hv = 0\n",
+    "    for i in m:\n",
+    "        hv = ((hv << 4) ^ (hv >> 1) ^ i) & 0xff\n",
+    "\n",
+    "    return hv"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Thanks to the fact that qlasskit function are standard python functions, we can call the `original_f` to perform some kind of analysis on the hash function. Since the input space is tiny (it is a toy hash function), we can detect if the hash function is uniform (if it maps equally to the output space)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Hash function output space: 256\n"
+     ]
+    }
+   ],
+   "source": [
+    "from collections import Counter\n",
+    "\n",
+    "d = Counter(hex(hash_simp.original_f((x, y))) for x in range(2**4) for y in range(2**4))\n",
+    "\n",
+    "print('Hash function output space:', len(d))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We got that `hash_simp` is following an uniform distribution. \n",
+    "\n",
+    "We now can use our quantum function as an oracle for a Grover search, in order to find which input maps to the value `ca`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit.algorithms import Grover\n",
+    "\n",
+    "q_algo = Grover(hash_simp, Qint8(0xca))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can use our prefered framework and simulator for sampling the result; this is an example using `qiskit` with `aer_simulator`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit import Aer, QuantumCircuit, transpile\n",
+    "from qiskit.visualization import plot_histogram\n",
+    "\n",
+    "qc = q_algo.export('qiskit')\n",
+    "qc.measure_all()\n",
+    "simulator = Aer.get_backend(\"aer_simulator\")\n",
+    "circ = transpile(qc, simulator)\n",
+    "result = simulator.run(circ).result()\n",
+    "counts = result.get_counts(circ)\n",
+    "\n",
+    "counts_readable = q_algo.decode_counts(counts, discard_lower=5)\n",
+    "plot_histogram(counts_readable)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We now double check using `original_f`; calling it with the tuple `(12,12)` must result in the hash value `0xca`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0xca\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(hex(hash_simp.original_f((12,12))))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "qlasskit_310-env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/_sources/example_grover_subset.ipynb.txt b/_sources/example_grover_subset.ipynb.txt
new file mode 100644
index 00000000..8fdcb820
--- /dev/null
+++ b/_sources/example_grover_subset.ipynb.txt
@@ -0,0 +1,108 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Grover search: subset problem\n",
+    "\n",
+    "We define a function named `subset_sum(i,j)` that returns the sum of the elements `i` and `j` of a list `l`. We want to use a Grover search to find which `i` `j` combination led to a given value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit import qlassf, Qint2, Qint3\n",
+    "from typing import Tuple\n",
+    "\n",
+    "@qlassf\n",
+    "def subset_sum(ii: Tuple[Qint2, Qint2]) -> Qint3:\n",
+    "    l = [0, 5, 2, 3]\n",
+    "    return l[ii[0]] + l[ii[1]] if ii[0] != ii[1] else 0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We now can use our quantum function as an oracle for a Grover search. For instance, we want to find the input value that produce the value `7`. Since we know that there are at least two result (`(i,j)` and `(j,i)`), we set `n_matching=2`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit.algorithms import Grover\n",
+    "\n",
+    "q_algo = Grover(subset_sum, Qint3(7), n_matching=2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can use our prefered framework and simulator for sampling the result; this is an example using `qiskit` with `aer_simulator`.\n",
+    "\n",
+    "In the output histogram, it's now evident that the input leading to a value of `7` are the tuples `(1,2)` and `(2,1)` (5+2 and 2+5), aligning with our expectations.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit import Aer, QuantumCircuit, transpile\n",
+    "from qiskit.visualization import plot_histogram\n",
+    "\n",
+    "qc = q_algo.export('qiskit')\n",
+    "qc.measure_all()\n",
+    "simulator = Aer.get_backend(\"aer_simulator\")\n",
+    "circ = transpile(qc, simulator)\n",
+    "result = simulator.run(circ).result()\n",
+    "counts = result.get_counts(circ)\n",
+    "\n",
+    "counts_readable = q_algo.decode_counts(counts)\n",
+    "plot_histogram(counts_readable)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "qlasskit_310-env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/_sources/example_grover_sudoku.ipynb.txt b/_sources/example_grover_sudoku.ipynb.txt
new file mode 100644
index 00000000..39d99b4e
--- /dev/null
+++ b/_sources/example_grover_sudoku.ipynb.txt
@@ -0,0 +1,99 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Grover search: sudoku solver\n",
+    "\n",
+    "In this example we are going to solve a sudoku puzzle. Since we have few qubits, we need to simplify the puzzle and so we use a 2x2 matrix where a valid solution is when in every row and every column there are no repeated values (`0` or `1`). We encode these xor-ing the values for each row and column. \n",
+    "Since we want a specific solution, we add a constraint `constr`: we want the `[0][0]` element to be `True`.\n",
+    "\n",
+    "We instantiate the `Grover` algorithm without value, since sudoku_check is already an oracle."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit import qlassf, Qint2, Qint4, Qmatrix\n",
+    "from qlasskit.algorithms import Grover\n",
+    "\n",
+    "@qlassf\n",
+    "def sudoku_check(m: Qmatrix[bool,2,2]) -> bool:\n",
+    "    constr = m[0][0]\n",
+    "    sub0 = (m[0][0] ^ m[0][1])\n",
+    "    sub1 = (m[1][0] ^ m[1][1])    \n",
+    "    sub2 = (m[0][0] ^ m[1][0])\n",
+    "    sub3 = (m[0][1] ^ m[1][1])\n",
+    "    return sub0 and sub1 and sub2 and sub3 and constr\n",
+    "\n",
+    "q_algo = Grover(sudoku_check)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can use our prefered framework and simulator for sampling the result; this is an example using `qiskit` with `aer_simulator`.\n",
+    "\n",
+    "We obtain that the solution for this puzzle is the matrix `[[True, False], [False, True]]`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit import Aer, QuantumCircuit, transpile\n",
+    "from qiskit.visualization import plot_histogram\n",
+    "\n",
+    "qc = q_algo.export('qiskit')\n",
+    "qc.measure_all()\n",
+    "simulator = Aer.get_backend(\"aer_simulator\")\n",
+    "circ = transpile(qc, simulator)\n",
+    "result = simulator.run(circ).result()\n",
+    "counts = result.get_counts(circ)\n",
+    "\n",
+    "counts_readable = q_algo.decode_counts(counts, discard_lower=20)\n",
+    "plot_histogram(counts_readable)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "qlasskit_310-env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/_sources/example_unitary_of_f.ipynb.txt b/_sources/example_unitary_of_f.ipynb.txt
new file mode 100644
index 00000000..9173b846
--- /dev/null
+++ b/_sources/example_unitary_of_f.ipynb.txt
@@ -0,0 +1,114 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Unitary of qlasskit function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "QlassF<f>(a:bool, b:bool) -> bool:\n",
+      "\t_ret = a ^ ~b\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 371.107x367.889 with 1 Axes>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit import Aer, QuantumCircuit, transpile, execute\n",
+    "from qiskit.visualization import array_to_latex\n",
+    "from qlasskit import qlassf\n",
+    "\n",
+    "@qlassf\n",
+    "def f(a: bool, b: bool) -> bool:\n",
+    "    return a ^ (not b)\n",
+    "\n",
+    "print(f\"\\n{f}\\n\")\n",
+    "\n",
+    "qc = QuantumCircuit(f.num_qubits, f.num_qubits)\n",
+    "qc.append(f.gate(), f.qubits)\n",
+    "\n",
+    "qc.decompose().draw('mpl')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "$$\n",
+       "\n",
+       "\\begin{bmatrix}\n",
+       "0 & 0 & 0 & 0 & 1 & 0 & 0 & 0  \\\\\n",
+       " 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0  \\\\\n",
+       " 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0  \\\\\n",
+       " 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1  \\\\\n",
+       " 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0  \\\\\n",
+       " 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0  \\\\\n",
+       " 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0  \\\\\n",
+       " 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0  \\\\\n",
+       " \\end{bmatrix}\n",
+       "$$"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Latex object>"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "simulator = Aer.get_backend('unitary_simulator')\n",
+    "job = execute(qc, simulator, shots=8192)\n",
+    "result = job.result()\n",
+    "array_to_latex(result.get_unitary(qc,3), max_size=16)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "qlasskit_310-env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/_sources/generated/qlasskit.algorithms.grover.Grover.rst.txt b/_sources/generated/qlasskit.algorithms.grover.Grover.rst.txt
new file mode 100644
index 00000000..c5426915
--- /dev/null
+++ b/_sources/generated/qlasskit.algorithms.grover.Grover.rst.txt
@@ -0,0 +1,40 @@
+qlasskit.algorithms.grover.Grover
+=================================
+
+.. currentmodule:: qlasskit.algorithms.grover
+
+.. autoclass:: Grover
+
+   
+   .. automethod:: __init__
+
+   
+   .. rubric:: Methods
+
+   .. autosummary::
+   
+      ~Grover.__init__
+      ~Grover.circuit
+      ~Grover.decode_counts
+      ~Grover.decode_output
+      ~Grover.draw
+      ~Grover.encode_input
+      ~Grover.export
+      ~Grover.gate
+   
+   
+
+   
+   
+   .. rubric:: Attributes
+
+   .. autosummary::
+   
+      ~Grover.input_qubits
+      ~Grover.input_size
+      ~Grover.num_qubits
+      ~Grover.output_qubits
+      ~Grover.output_size
+      ~Grover.qubits
+   
+   
\ No newline at end of file
diff --git a/_sources/generated/qlasskit.algorithms.qalgorithm.rst.txt b/_sources/generated/qlasskit.algorithms.qalgorithm.rst.txt
new file mode 100644
index 00000000..d819a261
--- /dev/null
+++ b/_sources/generated/qlasskit.algorithms.qalgorithm.rst.txt
@@ -0,0 +1,41 @@
+qlasskit.algorithms.qalgorithm
+==============================
+
+.. automodule:: qlasskit.algorithms.qalgorithm
+
+   
+   
+   
+
+   
+   
+   .. rubric:: Functions
+
+   .. autosummary::
+   
+      oraclize
+   
+   
+
+   
+   
+   .. rubric:: Classes
+
+   .. autosummary::
+   
+      QAlgorithm
+   
+   
+
+   
+   
+   .. rubric:: Exceptions
+
+   .. autosummary::
+   
+      ConstantOracleException
+   
+   
+
+
+
diff --git a/_sources/generated/qlasskit.qcircuit.gates.rst.txt b/_sources/generated/qlasskit.qcircuit.gates.rst.txt
new file mode 100644
index 00000000..35c21029
--- /dev/null
+++ b/_sources/generated/qlasskit.qcircuit.gates.rst.txt
@@ -0,0 +1,49 @@
+qlasskit.qcircuit.gates
+=======================
+
+.. automodule:: qlasskit.qcircuit.gates
+
+   
+   
+   
+
+   
+   
+   .. rubric:: Functions
+
+   .. autosummary::
+   
+      apply
+   
+   
+
+   
+   
+   .. rubric:: Classes
+
+   .. autosummary::
+   
+      Barrier
+      CCX
+      CX
+      H
+      MCX
+      MCtrl
+      NopGate
+      QControlledGate
+      QGate
+      S
+      T
+      Toffoli
+      X
+      Y
+      Z
+   
+   
+
+   
+   
+   
+
+
+
diff --git a/_sources/generated/qlasskit.qcircuit.qcircuit.QCircuit.rst.txt b/_sources/generated/qlasskit.qcircuit.qcircuit.QCircuit.rst.txt
new file mode 100644
index 00000000..88d70e89
--- /dev/null
+++ b/_sources/generated/qlasskit.qcircuit.qcircuit.QCircuit.rst.txt
@@ -0,0 +1,45 @@
+qlasskit.qcircuit.qcircuit.QCircuit
+===================================
+
+.. currentmodule:: qlasskit.qcircuit.qcircuit
+
+.. autoclass:: QCircuit
+
+   
+   .. automethod:: __init__
+
+   
+   .. rubric:: Methods
+
+   .. autosummary::
+   
+      ~QCircuit.__init__
+      ~QCircuit.add_qubit
+      ~QCircuit.append
+      ~QCircuit.barrier
+      ~QCircuit.ccx
+      ~QCircuit.copy
+      ~QCircuit.cx
+      ~QCircuit.draw
+      ~QCircuit.export
+      ~QCircuit.get_key_by_index
+      ~QCircuit.h
+      ~QCircuit.mctrl
+      ~QCircuit.mcx
+      ~QCircuit.s
+      ~QCircuit.t
+      ~QCircuit.x
+      ~QCircuit.y
+      ~QCircuit.z
+   
+   
+
+   
+   
+   .. rubric:: Attributes
+
+   .. autosummary::
+   
+      ~QCircuit.num_gates
+   
+   
\ No newline at end of file
diff --git a/_sources/generated/qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.rst.txt b/_sources/generated/qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.rst.txt
new file mode 100644
index 00000000..fc0e682b
--- /dev/null
+++ b/_sources/generated/qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.rst.txt
@@ -0,0 +1,40 @@
+qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper
+=================================================
+
+.. currentmodule:: qlasskit.qcircuit.qcircuitwrapper
+
+.. autoclass:: QCircuitWrapper
+
+   
+   .. automethod:: __init__
+
+   
+   .. rubric:: Methods
+
+   .. autosummary::
+   
+      ~QCircuitWrapper.__init__
+      ~QCircuitWrapper.circuit
+      ~QCircuitWrapper.decode_counts
+      ~QCircuitWrapper.decode_output
+      ~QCircuitWrapper.draw
+      ~QCircuitWrapper.encode_input
+      ~QCircuitWrapper.export
+      ~QCircuitWrapper.gate
+   
+   
+
+   
+   
+   .. rubric:: Attributes
+
+   .. autosummary::
+   
+      ~QCircuitWrapper.input_qubits
+      ~QCircuitWrapper.input_size
+      ~QCircuitWrapper.num_qubits
+      ~QCircuitWrapper.output_qubits
+      ~QCircuitWrapper.output_size
+      ~QCircuitWrapper.qubits
+   
+   
\ No newline at end of file
diff --git a/_sources/generated/qlasskit.qlassfun.QlassF.rst.txt b/_sources/generated/qlasskit.qlassfun.QlassF.rst.txt
new file mode 100644
index 00000000..148773ed
--- /dev/null
+++ b/_sources/generated/qlasskit.qlassfun.QlassF.rst.txt
@@ -0,0 +1,52 @@
+qlasskit.qlassfun.QlassF
+========================
+
+.. currentmodule:: qlasskit.qlassfun
+
+.. autoclass:: QlassF
+
+   
+   .. automethod:: __init__
+
+   
+   .. rubric:: Methods
+
+   .. autosummary::
+   
+      ~QlassF.__init__
+      ~QlassF.bind
+      ~QlassF.circuit
+      ~QlassF.compile
+      ~QlassF.decode_counts
+      ~QlassF.decode_output
+      ~QlassF.draw
+      ~QlassF.encode_input
+      ~QlassF.export
+      ~QlassF.f
+      ~QlassF.from_function
+      ~QlassF.gate
+      ~QlassF.to_logicfun
+      ~QlassF.truth_table
+      ~QlassF.truth_table_header
+   
+   
+
+   
+   
+   .. rubric:: Attributes
+
+   .. autosummary::
+   
+      ~QlassF.input_qubits
+      ~QlassF.input_size
+      ~QlassF.num_qubits
+      ~QlassF.output_qubits
+      ~QlassF.output_size
+      ~QlassF.qubits
+      ~QlassF.name
+      ~QlassF.original_f
+      ~QlassF.args
+      ~QlassF.returns
+      ~QlassF.expressions
+   
+   
\ No newline at end of file
diff --git a/_sources/generated/qlasskit.qlassfun.qlassf.rst.txt b/_sources/generated/qlasskit.qlassfun.qlassf.rst.txt
new file mode 100644
index 00000000..51d99df6
--- /dev/null
+++ b/_sources/generated/qlasskit.qlassfun.qlassf.rst.txt
@@ -0,0 +1,6 @@
+qlasskit.qlassfun.qlassf
+========================
+
+.. currentmodule:: qlasskit.qlassfun
+
+.. autofunction:: qlassf
\ No newline at end of file
diff --git a/_sources/generated/qlasskit.qlassfun.qlassfa.rst.txt b/_sources/generated/qlasskit.qlassfun.qlassfa.rst.txt
new file mode 100644
index 00000000..cb63d945
--- /dev/null
+++ b/_sources/generated/qlasskit.qlassfun.qlassfa.rst.txt
@@ -0,0 +1,6 @@
+qlasskit.qlassfun.qlassfa
+=========================
+
+.. currentmodule:: qlasskit.qlassfun
+
+.. autofunction:: qlassfa
\ No newline at end of file
diff --git a/_sources/how_it_works.ipynb.txt b/_sources/how_it_works.ipynb.txt
new file mode 100644
index 00000000..ace3f58c
--- /dev/null
+++ b/_sources/how_it_works.ipynb.txt
@@ -0,0 +1,250 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# How it works\n",
+    "\n",
+    "To convert Python code into a quantum circuit, qlasskit implements a series of transformations:\n",
+    "\n",
+    "1. It begins with the Python *AST* (Abstract Syntax Tree), converting it into a more streamlined form using the `ast2ast` module. \n",
+    "2. Next, the streamlined AST is translated into *boolean expressions* as an intermediate step by the `ast2logic` module. \n",
+    "During this phase, boolean expressions are refined and optimized in preparation for the final transformation.\n",
+    "3. Finally, the `compiler` module takes these optimized boolean expressions and compiles them into a \n",
+    "*quantum circuit*.\n",
+    "\n",
+    "Unlike other libraries that translate individual operations into quantum circuits before combining them, \n",
+    "qlasskit constructs a singular boolean expression for each output qubit of the entire function. \n",
+    "This unique approach facilitates advanced optimization leveraging boolean algebraic properties.\n",
+    "\n",
+    "\n",
+    "For instance, let assume we have the following function:\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit import qlassf, Qint2, Qint4\n",
+    "from qiskit import QuantumCircuit\n",
+    "\n",
+    "@qlassf\n",
+    "def f_comp(b: bool, n: Qint2) -> Qint2:\n",
+    "      for i in range(3):\n",
+    "            n += (1 if b else 2)\n",
+    "      return n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If we decompose the algorithm in 3 separate additions and we compile them separately, we obtain the following circuit:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Operations: OrderedDict([('cx', 12), ('barrier', 3), ('x', 3), ('ccx', 3)])\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1876.11x785.944 with 1 Axes>"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@qlassf\n",
+    "def f1(b: bool, n: Qint2) -> Qint2:\n",
+    "    return n + (1 if b else 2)\n",
+    "\n",
+    "qc = QuantumCircuit(f_comp.num_qubits * 2 - 1)\n",
+    "\n",
+    "for i in range(3):\n",
+    "    qc.barrier(label=f\"it_{i}\")\n",
+    "    qc.append(f1.gate(), [0] + list(range(1 + i * 2, 5 + i * 2)))\n",
+    "\n",
+    "print('Operations:', qc.decompose().count_ops())\n",
+    "qc.decompose().draw(\"mpl\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "While if we compile the whole function to a quantum circuit using qlasskit, we obtain the following quantum circuit:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Operations: OrderedDict([('cx', 4), ('x', 1), ('ccx', 1)])\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 621.941x451.5 with 1 Axes>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc = QuantumCircuit(f_comp.num_qubits)\n",
+    "qc.append(f_comp.gate(), f_comp.qubits)\n",
+    "\n",
+    "print('Operations:', qc.decompose().count_ops())\n",
+    "qc.decompose().draw(\"mpl\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As we can see from the circuit drawings, qlasskit approach needs half the number of qubits and half the number of gates."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## AST Traslator\n",
+    "Given a python function, the `qlasskit.ast2logic` module walks its syntax tree translating all the statements / \n",
+    "expressions to boolean expressions.\n",
+    "\n",
+    "\n",
+    "For instance, the following function:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@qlassf\n",
+    "def f(n: Qint4) -> bool:\n",
+    "        return n == 3       "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Is translated to this boolean expression:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[(_ret, n.0 & n.1 & ~n.2 & ~n.3)]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f.expressions)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## Compiler\n",
+    "\n",
+    "The boolean expressions are then being fed to the `qlasskit.compiler`` which compiles boolean expressions\n",
+    "to invertible circuits, introducing auxiliary qubits. In this step, the compiler will automatically uncompute \n",
+    "auxiliary qubits in order to reduce the number of qubits needed and the circuit footprint. \n",
+    "\n",
+    "For the compilation, two backends are supported:\n",
+    "\n",
+    "- InternalCompiler\n",
+    "- Tweedledum.xag_synth\n",
+    "\n",
+    "\n",
+    "## Result \n",
+    "\n",
+    "The result of the compiler is a quantum circuit represented with qlasskit `QCircuit`. This circuit\n",
+    "can now be exported to one of the supported framework as a gate or as a standalone circuit.\n",
+    "\n",
+    "\n",
+    "The previous example function `f`, is translated to the following quantum circuit: the \n",
+    "result is available at qubit `q6`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 705.552x618.722 with 1 Axes>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f.export().draw('mpl')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "qlasskit_310-env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt
new file mode 100644
index 00000000..aa6ab8db
--- /dev/null
+++ b/_sources/index.rst.txt
@@ -0,0 +1,33 @@
+Qlasskit
+====================================
+
+Qlasskit is a Python library that allows quantum developers to write classical algorithms in pure 
+Python and translate them into unitary operators (gates) for use in quantum circuits.
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Qlasskit
+
+   quickstart.ipynb   
+   how_it_works.ipynb
+   supported
+   algorithms
+   api
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Examples
+
+   example_grover.ipynb
+   example_grover_subset.ipynb
+   example_grover_hash.ipynb
+   example_grover_sudoku.ipynb
+   example_unitary_of_f.ipynb
+
+
+Indices and tables
+==================
+
+* :ref:`genindex`
+* :ref:`modindex`
+* :ref:`search`
diff --git a/_sources/quickstart.ipynb.txt b/_sources/quickstart.ipynb.txt
new file mode 100644
index 00000000..c78f106f
--- /dev/null
+++ b/_sources/quickstart.ipynb.txt
@@ -0,0 +1,136 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Quickstart\n",
+    "\n",
+    "First install qlasskit using pip.\n",
+    "\n",
+    "```pip install qlasskit```\n",
+    "\n",
+    "We now define a qlassf function that sums two numbers:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit import qlassf, Qint2\n",
+    "\n",
+    "@qlassf \n",
+    "def sum_two_numbers(a: Qint2, b: Qint2) -> Qint2:\n",
+    "    return a + b"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now export the resulting quantum circuit to any supported framework:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 538.33x535.111 with 1 Axes>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circuit = sum_two_numbers.export('qiskit')\n",
+    "circuit.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The qlassf function can be also exported as a gate, if the destination framwork supports it. We can use `encode_input` and `decode_output` in order to conver from/to high level types of qlasskit without worrying about the binary representation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 789.163x618.722 with 1 Axes>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit import QuantumCircuit\n",
+    "\n",
+    "qc = QuantumCircuit(sum_two_numbers.num_qubits,len(sum_two_numbers.output_qubits))\n",
+    "\n",
+    "qc.initialize(sum_two_numbers.encode_input(Qint2(1), Qint2(2)), sum_two_numbers.input_qubits)\n",
+    "qc.append(sum_two_numbers.gate('qiskit'), sum_two_numbers.qubits)\n",
+    "qc.measure(sum_two_numbers.output_qubits, range(len(sum_two_numbers.output_qubits)))\n",
+    "qc.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit import Aer, QuantumCircuit, transpile\n",
+    "from qiskit.visualization import plot_histogram\n",
+    "\n",
+    "simulator = Aer.get_backend(\"aer_simulator\")\n",
+    "circ = transpile(qc, simulator)\n",
+    "result = simulator.run(circ).result()\n",
+    "counts = result.get_counts(circ)\n",
+    "\n",
+    "counts_readable = sum_two_numbers.decode_counts(counts)\n",
+    "plot_histogram(counts_readable)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/_sources/supported.rst.txt b/_sources/supported.rst.txt
new file mode 100644
index 00000000..b9dbf439
--- /dev/null
+++ b/_sources/supported.rst.txt
@@ -0,0 +1,253 @@
+Supported python subset
+====================================
+
+Qlasskit supports a subset of python. This subset will be expanded, but it is
+limited by the linearity of quantum circuits and by the number of qubits.
+
+The structure of a qlasskit function has the following pattern:
+
+.. code-block:: python
+
+   @qlasskit
+   def f(param: type, [...param: type]) -> type:
+      statement
+      ...
+      statement
+
+
+Types
+-----
+
+All types has a static size. 
+
+bool
+^^^^
+
+Boolean type.
+
+
+Qint
+^^^^
+
+Unsigned integers; this type has subtypes for different Qint sizes (Qint2, Qint4, Qint8, Qint12, Qint16). 
+Single bit of the Qint are accessible by the subscript operator `[]`.
+
+
+Tuple
+^^^^^
+
+Container type holding different types.
+
+
+List
+^^^^
+
+Qlist[T, size] denotes a fixed-size list in qlasskit. 
+For example, the list `[1,2,3]` is typed as `Qlist[Qint2,3]`.
+
+
+Matrix
+^^^^
+
+Qmatrix[T, m, n] denotes a fixed-size list in qlasskit. 
+For example, the matrix `[[1,2],[3,4]]` is typed as `Qmatrix[Qint2,2,2]`.
+
+
+
+
+
+Expressions
+-----------
+
+Constants
+^^^^^^^^^^^^^
+
+.. code-block:: python
+
+   True
+
+.. code-block:: python
+
+   42
+
+
+Tuple
+^^^^^
+
+.. code-block:: python
+
+   (a, b)
+
+List (fixed size)
+^^^^^^^^^^^^^^^^^
+
+.. code-block:: python
+   
+   [a, b]
+
+
+2D Matrix (fixed size)
+^^^^^^^^^^^^^^^^^
+
+.. code-block:: python
+   
+   [[a, b], [c,d]]
+
+
+Subscript
+^^^^^^^^^
+
+.. code-block:: python
+
+   a[0]
+
+Boolean operators
+^^^^^^^^^^^^^^^^^
+
+.. code-block:: python
+
+   not a
+
+.. code-block:: python
+
+   a and b
+
+.. code-block:: python
+
+   a or b 
+
+
+
+If expressions
+^^^^^^^^^^^^^^
+
+.. code-block:: python
+
+   a if b else c
+
+Comparators
+^^^^^^^^^^^
+
+.. code-block:: python
+
+   a > b or b <= c and c == d or c != a
+
+
+Unary Op
+^^^^^^^^^
+
+.. code-block:: python
+
+   ~a
+
+
+
+Bin Op
+^^^^^^^^^
+
+.. code-block:: python
+
+   a << 1
+
+.. code-block:: python
+
+   a >> 2
+
+.. code-block:: python
+
+   a + b
+
+.. code-block:: python
+
+   a - b
+
+.. code-block:: python
+
+   a * b
+
+   
+
+Function call
+^^^^^^^^^^^^^
+
+Bultin functions:
+- `print()`: debug function, ignore by conversion
+- `len(Tuple)`, `len(Qlist)``: returns the length of a tuple
+- `max(a, b, ...)`, `max(Tuple)`, `max(Qlist)`: returns the max of a tuple
+- `min(a, b, ...)`, `min(Tuple)`, `min(Qlist)`: returns the min of a tuple
+- `sum(Tuple)`, `sum(Qlist)`: returns the sum of the elemnts of a tuple / list
+- `all(Tuple)`, `all(Qlist)`: returns True if all of the elemnts are True
+- `any(Tuple)`, `any(Qlist)`: returns True if any of the elemnts are True
+
+
+
+Statements 
+----------
+
+Assign
+^^^^^^
+
+.. code-block:: python
+
+   c = not a
+
+Return
+^^^^^^
+
+.. code-block:: python
+
+   return b+1
+
+
+For loop
+^^^^^^^^
+
+.. code-block:: python
+
+   for i in range(4):
+      a += i
+
+
+.. note::
+   Please note that in qlasskit, for loops are unrolled during compilation. Therefore, 
+   it is essential that the number of iterations for each for loop is known at the 
+   time of compilation.
+
+Function def
+^^^^^^^^^^^^
+
+.. code-block:: python
+
+   def f(t: Qlist[Qint4,2]) -> Qint4:
+      return t[0] + t[1]
+
+
+If then else
+^^^^^^^^^^^^
+
+.. code-block:: python
+
+   c = 0
+   if cond:
+      c += 12
+   else:
+      c += 13
+
+.. note::
+   At present, the if-then-else statement in qlasskit is designed to support branch bodies 
+   that exclusively contain assignment statements.
+
+
+
+Quantum Hybrid
+---------------
+
+In a qlassf function, you have the option to utilize quantum gates through the Q module. It's 
+important to keep in mind that incorporating quantum gates within a qlasskit function leads 
+to a Python function that exhibits distinct behaviors compared to its quantum counterpart.
+
+.. code-block:: python
+
+   def bell(a: bool, b: bool) -> bool:
+      return Q.CX(Q.H(a), b)
+
diff --git a/_static/_sphinx_javascript_frameworks_compat.js b/_static/_sphinx_javascript_frameworks_compat.js
new file mode 100644
index 00000000..81415803
--- /dev/null
+++ b/_static/_sphinx_javascript_frameworks_compat.js
@@ -0,0 +1,123 @@
+/* Compatability shim for jQuery and underscores.js.
+ *
+ * Copyright Sphinx contributors
+ * Released under the two clause BSD licence
+ */
+
+/**
+ * small helper function to urldecode strings
+ *
+ * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL
+ */
+jQuery.urldecode = function(x) {
+    if (!x) {
+        return x
+    }
+    return decodeURIComponent(x.replace(/\+/g, ' '));
+};
+
+/**
+ * small helper function to urlencode strings
+ */
+jQuery.urlencode = encodeURIComponent;
+
+/**
+ * This function returns the parsed url parameters of the
+ * current request. Multiple values per key are supported,
+ * it will always return arrays of strings for the value parts.
+ */
+jQuery.getQueryParameters = function(s) {
+    if (typeof s === 'undefined')
+        s = document.location.search;
+    var parts = s.substr(s.indexOf('?') + 1).split('&');
+    var result = {};
+    for (var i = 0; i < parts.length; i++) {
+        var tmp = parts[i].split('=', 2);
+        var key = jQuery.urldecode(tmp[0]);
+        var value = jQuery.urldecode(tmp[1]);
+        if (key in result)
+            result[key].push(value);
+        else
+            result[key] = [value];
+    }
+    return result;
+};
+
+/**
+ * highlight a given string on a jquery object by wrapping it in
+ * span elements with the given class name.
+ */
+jQuery.fn.highlightText = function(text, className) {
+    function highlight(node, addItems) {
+        if (node.nodeType === 3) {
+            var val = node.nodeValue;
+            var pos = val.toLowerCase().indexOf(text);
+            if (pos >= 0 &&
+                !jQuery(node.parentNode).hasClass(className) &&
+                !jQuery(node.parentNode).hasClass("nohighlight")) {
+                var span;
+                var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg");
+                if (isInSVG) {
+                    span = document.createElementNS("http://www.w3.org/2000/svg", "tspan");
+                } else {
+                    span = document.createElement("span");
+                    span.className = className;
+                }
+                span.appendChild(document.createTextNode(val.substr(pos, text.length)));
+                node.parentNode.insertBefore(span, node.parentNode.insertBefore(
+                    document.createTextNode(val.substr(pos + text.length)),
+                    node.nextSibling));
+                node.nodeValue = val.substr(0, pos);
+                if (isInSVG) {
+                    var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect");
+                    var bbox = node.parentElement.getBBox();
+                    rect.x.baseVal.value = bbox.x;
+                    rect.y.baseVal.value = bbox.y;
+                    rect.width.baseVal.value = bbox.width;
+                    rect.height.baseVal.value = bbox.height;
+                    rect.setAttribute('class', className);
+                    addItems.push({
+                        "parent": node.parentNode,
+                        "target": rect});
+                }
+            }
+        }
+        else if (!jQuery(node).is("button, select, textarea")) {
+            jQuery.each(node.childNodes, function() {
+                highlight(this, addItems);
+            });
+        }
+    }
+    var addItems = [];
+    var result = this.each(function() {
+        highlight(this, addItems);
+    });
+    for (var i = 0; i < addItems.length; ++i) {
+        jQuery(addItems[i].parent).before(addItems[i].target);
+    }
+    return result;
+};
+
+/*
+ * backward compatibility for jQuery.browser
+ * This will be supported until firefox bug is fixed.
+ */
+if (!jQuery.browser) {
+    jQuery.uaMatch = function(ua) {
+        ua = ua.toLowerCase();
+
+        var match = /(chrome)[ \/]([\w.]+)/.exec(ua) ||
+            /(webkit)[ \/]([\w.]+)/.exec(ua) ||
+            /(opera)(?:.*version|)[ \/]([\w.]+)/.exec(ua) ||
+            /(msie) ([\w.]+)/.exec(ua) ||
+            ua.indexOf("compatible") < 0 && /(mozilla)(?:.*? rv:([\w.]+)|)/.exec(ua) ||
+            [];
+
+        return {
+            browser: match[ 1 ] || "",
+            version: match[ 2 ] || "0"
+        };
+    };
+    jQuery.browser = {};
+    jQuery.browser[jQuery.uaMatch(navigator.userAgent).browser] = true;
+}
diff --git a/_static/basic.css b/_static/basic.css
new file mode 100644
index 00000000..30fee9d0
--- /dev/null
+++ b/_static/basic.css
@@ -0,0 +1,925 @@
+/*
+ * basic.css
+ * ~~~~~~~~~
+ *
+ * Sphinx stylesheet -- basic theme.
+ *
+ * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+
+/* -- main layout ----------------------------------------------------------- */
+
+div.clearer {
+    clear: both;
+}
+
+div.section::after {
+    display: block;
+    content: '';
+    clear: left;
+}
+
+/* -- relbar ---------------------------------------------------------------- */
+
+div.related {
+    width: 100%;
+    font-size: 90%;
+}
+
+div.related h3 {
+    display: none;
+}
+
+div.related ul {
+    margin: 0;
+    padding: 0 0 0 10px;
+    list-style: none;
+}
+
+div.related li {
+    display: inline;
+}
+
+div.related li.right {
+    float: right;
+    margin-right: 5px;
+}
+
+/* -- sidebar --------------------------------------------------------------- */
+
+div.sphinxsidebarwrapper {
+    padding: 10px 5px 0 10px;
+}
+
+div.sphinxsidebar {
+    float: left;
+    width: 230px;
+    margin-left: -100%;
+    font-size: 90%;
+    word-wrap: break-word;
+    overflow-wrap : break-word;
+}
+
+div.sphinxsidebar ul {
+    list-style: none;
+}
+
+div.sphinxsidebar ul ul,
+div.sphinxsidebar ul.want-points {
+    margin-left: 20px;
+    list-style: square;
+}
+
+div.sphinxsidebar ul ul {
+    margin-top: 0;
+    margin-bottom: 0;
+}
+
+div.sphinxsidebar form {
+    margin-top: 10px;
+}
+
+div.sphinxsidebar input {
+    border: 1px solid #98dbcc;
+    font-family: sans-serif;
+    font-size: 1em;
+}
+
+div.sphinxsidebar #searchbox form.search {
+    overflow: hidden;
+}
+
+div.sphinxsidebar #searchbox input[type="text"] {
+    float: left;
+    width: 80%;
+    padding: 0.25em;
+    box-sizing: border-box;
+}
+
+div.sphinxsidebar #searchbox input[type="submit"] {
+    float: left;
+    width: 20%;
+    border-left: none;
+    padding: 0.25em;
+    box-sizing: border-box;
+}
+
+
+img {
+    border: 0;
+    max-width: 100%;
+}
+
+/* -- search page ----------------------------------------------------------- */
+
+ul.search {
+    margin: 10px 0 0 20px;
+    padding: 0;
+}
+
+ul.search li {
+    padding: 5px 0 5px 20px;
+    background-image: url(file.png);
+    background-repeat: no-repeat;
+    background-position: 0 7px;
+}
+
+ul.search li a {
+    font-weight: bold;
+}
+
+ul.search li p.context {
+    color: #888;
+    margin: 2px 0 0 30px;
+    text-align: left;
+}
+
+ul.keywordmatches li.goodmatch a {
+    font-weight: bold;
+}
+
+/* -- index page ------------------------------------------------------------ */
+
+table.contentstable {
+    width: 90%;
+    margin-left: auto;
+    margin-right: auto;
+}
+
+table.contentstable p.biglink {
+    line-height: 150%;
+}
+
+a.biglink {
+    font-size: 1.3em;
+}
+
+span.linkdescr {
+    font-style: italic;
+    padding-top: 5px;
+    font-size: 90%;
+}
+
+/* -- general index --------------------------------------------------------- */
+
+table.indextable {
+    width: 100%;
+}
+
+table.indextable td {
+    text-align: left;
+    vertical-align: top;
+}
+
+table.indextable ul {
+    margin-top: 0;
+    margin-bottom: 0;
+    list-style-type: none;
+}
+
+table.indextable > tbody > tr > td > ul {
+    padding-left: 0em;
+}
+
+table.indextable tr.pcap {
+    height: 10px;
+}
+
+table.indextable tr.cap {
+    margin-top: 10px;
+    background-color: #f2f2f2;
+}
+
+img.toggler {
+    margin-right: 3px;
+    margin-top: 3px;
+    cursor: pointer;
+}
+
+div.modindex-jumpbox {
+    border-top: 1px solid #ddd;
+    border-bottom: 1px solid #ddd;
+    margin: 1em 0 1em 0;
+    padding: 0.4em;
+}
+
+div.genindex-jumpbox {
+    border-top: 1px solid #ddd;
+    border-bottom: 1px solid #ddd;
+    margin: 1em 0 1em 0;
+    padding: 0.4em;
+}
+
+/* -- domain module index --------------------------------------------------- */
+
+table.modindextable td {
+    padding: 2px;
+    border-collapse: collapse;
+}
+
+/* -- general body styles --------------------------------------------------- */
+
+div.body {
+    min-width: 360px;
+    max-width: 800px;
+}
+
+div.body p, div.body dd, div.body li, div.body blockquote {
+    -moz-hyphens: auto;
+    -ms-hyphens: auto;
+    -webkit-hyphens: auto;
+    hyphens: auto;
+}
+
+a.headerlink {
+    visibility: hidden;
+}
+
+a:visited {
+    color: #551A8B;
+}
+
+h1:hover > a.headerlink,
+h2:hover > a.headerlink,
+h3:hover > a.headerlink,
+h4:hover > a.headerlink,
+h5:hover > a.headerlink,
+h6:hover > a.headerlink,
+dt:hover > a.headerlink,
+caption:hover > a.headerlink,
+p.caption:hover > a.headerlink,
+div.code-block-caption:hover > a.headerlink {
+    visibility: visible;
+}
+
+div.body p.caption {
+    text-align: inherit;
+}
+
+div.body td {
+    text-align: left;
+}
+
+.first {
+    margin-top: 0 !important;
+}
+
+p.rubric {
+    margin-top: 30px;
+    font-weight: bold;
+}
+
+img.align-left, figure.align-left, .figure.align-left, object.align-left {
+    clear: left;
+    float: left;
+    margin-right: 1em;
+}
+
+img.align-right, figure.align-right, .figure.align-right, object.align-right {
+    clear: right;
+    float: right;
+    margin-left: 1em;
+}
+
+img.align-center, figure.align-center, .figure.align-center, object.align-center {
+  display: block;
+  margin-left: auto;
+  margin-right: auto;
+}
+
+img.align-default, figure.align-default, .figure.align-default {
+  display: block;
+  margin-left: auto;
+  margin-right: auto;
+}
+
+.align-left {
+    text-align: left;
+}
+
+.align-center {
+    text-align: center;
+}
+
+.align-default {
+    text-align: center;
+}
+
+.align-right {
+    text-align: right;
+}
+
+/* -- sidebars -------------------------------------------------------------- */
+
+div.sidebar,
+aside.sidebar {
+    margin: 0 0 0.5em 1em;
+    border: 1px solid #ddb;
+    padding: 7px;
+    background-color: #ffe;
+    width: 40%;
+    float: right;
+    clear: right;
+    overflow-x: auto;
+}
+
+p.sidebar-title {
+    font-weight: bold;
+}
+
+nav.contents,
+aside.topic,
+div.admonition, div.topic, blockquote {
+    clear: left;
+}
+
+/* -- topics ---------------------------------------------------------------- */
+
+nav.contents,
+aside.topic,
+div.topic {
+    border: 1px solid #ccc;
+    padding: 7px;
+    margin: 10px 0 10px 0;
+}
+
+p.topic-title {
+    font-size: 1.1em;
+    font-weight: bold;
+    margin-top: 10px;
+}
+
+/* -- admonitions ----------------------------------------------------------- */
+
+div.admonition {
+    margin-top: 10px;
+    margin-bottom: 10px;
+    padding: 7px;
+}
+
+div.admonition dt {
+    font-weight: bold;
+}
+
+p.admonition-title {
+    margin: 0px 10px 5px 0px;
+    font-weight: bold;
+}
+
+div.body p.centered {
+    text-align: center;
+    margin-top: 25px;
+}
+
+/* -- content of sidebars/topics/admonitions -------------------------------- */
+
+div.sidebar > :last-child,
+aside.sidebar > :last-child,
+nav.contents > :last-child,
+aside.topic > :last-child,
+div.topic > :last-child,
+div.admonition > :last-child {
+    margin-bottom: 0;
+}
+
+div.sidebar::after,
+aside.sidebar::after,
+nav.contents::after,
+aside.topic::after,
+div.topic::after,
+div.admonition::after,
+blockquote::after {
+    display: block;
+    content: '';
+    clear: both;
+}
+
+/* -- tables ---------------------------------------------------------------- */
+
+table.docutils {
+    margin-top: 10px;
+    margin-bottom: 10px;
+    border: 0;
+    border-collapse: collapse;
+}
+
+table.align-center {
+    margin-left: auto;
+    margin-right: auto;
+}
+
+table.align-default {
+    margin-left: auto;
+    margin-right: auto;
+}
+
+table caption span.caption-number {
+    font-style: italic;
+}
+
+table caption span.caption-text {
+}
+
+table.docutils td, table.docutils th {
+    padding: 1px 8px 1px 5px;
+    border-top: 0;
+    border-left: 0;
+    border-right: 0;
+    border-bottom: 1px solid #aaa;
+}
+
+th {
+    text-align: left;
+    padding-right: 5px;
+}
+
+table.citation {
+    border-left: solid 1px gray;
+    margin-left: 1px;
+}
+
+table.citation td {
+    border-bottom: none;
+}
+
+th > :first-child,
+td > :first-child {
+    margin-top: 0px;
+}
+
+th > :last-child,
+td > :last-child {
+    margin-bottom: 0px;
+}
+
+/* -- figures --------------------------------------------------------------- */
+
+div.figure, figure {
+    margin: 0.5em;
+    padding: 0.5em;
+}
+
+div.figure p.caption, figcaption {
+    padding: 0.3em;
+}
+
+div.figure p.caption span.caption-number,
+figcaption span.caption-number {
+    font-style: italic;
+}
+
+div.figure p.caption span.caption-text,
+figcaption span.caption-text {
+}
+
+/* -- field list styles ----------------------------------------------------- */
+
+table.field-list td, table.field-list th {
+    border: 0 !important;
+}
+
+.field-list ul {
+    margin: 0;
+    padding-left: 1em;
+}
+
+.field-list p {
+    margin: 0;
+}
+
+.field-name {
+    -moz-hyphens: manual;
+    -ms-hyphens: manual;
+    -webkit-hyphens: manual;
+    hyphens: manual;
+}
+
+/* -- hlist styles ---------------------------------------------------------- */
+
+table.hlist {
+    margin: 1em 0;
+}
+
+table.hlist td {
+    vertical-align: top;
+}
+
+/* -- object description styles --------------------------------------------- */
+
+.sig {
+	font-family: 'Consolas', 'Menlo', 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', monospace;
+}
+
+.sig-name, code.descname {
+    background-color: transparent;
+    font-weight: bold;
+}
+
+.sig-name {
+	font-size: 1.1em;
+}
+
+code.descname {
+    font-size: 1.2em;
+}
+
+.sig-prename, code.descclassname {
+    background-color: transparent;
+}
+
+.optional {
+    font-size: 1.3em;
+}
+
+.sig-paren {
+    font-size: larger;
+}
+
+.sig-param.n {
+	font-style: italic;
+}
+
+/* C++ specific styling */
+
+.sig-inline.c-texpr,
+.sig-inline.cpp-texpr {
+	font-family: unset;
+}
+
+.sig.c   .k, .sig.c   .kt,
+.sig.cpp .k, .sig.cpp .kt {
+	color: #0033B3;
+}
+
+.sig.c   .m,
+.sig.cpp .m {
+	color: #1750EB;
+}
+
+.sig.c   .s, .sig.c   .sc,
+.sig.cpp .s, .sig.cpp .sc {
+	color: #067D17;
+}
+
+
+/* -- other body styles ----------------------------------------------------- */
+
+ol.arabic {
+    list-style: decimal;
+}
+
+ol.loweralpha {
+    list-style: lower-alpha;
+}
+
+ol.upperalpha {
+    list-style: upper-alpha;
+}
+
+ol.lowerroman {
+    list-style: lower-roman;
+}
+
+ol.upperroman {
+    list-style: upper-roman;
+}
+
+:not(li) > ol > li:first-child > :first-child,
+:not(li) > ul > li:first-child > :first-child {
+    margin-top: 0px;
+}
+
+:not(li) > ol > li:last-child > :last-child,
+:not(li) > ul > li:last-child > :last-child {
+    margin-bottom: 0px;
+}
+
+ol.simple ol p,
+ol.simple ul p,
+ul.simple ol p,
+ul.simple ul p {
+    margin-top: 0;
+}
+
+ol.simple > li:not(:first-child) > p,
+ul.simple > li:not(:first-child) > p {
+    margin-top: 0;
+}
+
+ol.simple p,
+ul.simple p {
+    margin-bottom: 0;
+}
+
+aside.footnote > span,
+div.citation > span {
+    float: left;
+}
+aside.footnote > span:last-of-type,
+div.citation > span:last-of-type {
+  padding-right: 0.5em;
+}
+aside.footnote > p {
+  margin-left: 2em;
+}
+div.citation > p {
+  margin-left: 4em;
+}
+aside.footnote > p:last-of-type,
+div.citation > p:last-of-type {
+    margin-bottom: 0em;
+}
+aside.footnote > p:last-of-type:after,
+div.citation > p:last-of-type:after {
+    content: "";
+    clear: both;
+}
+
+dl.field-list {
+    display: grid;
+    grid-template-columns: fit-content(30%) auto;
+}
+
+dl.field-list > dt {
+    font-weight: bold;
+    word-break: break-word;
+    padding-left: 0.5em;
+    padding-right: 5px;
+}
+
+dl.field-list > dd {
+    padding-left: 0.5em;
+    margin-top: 0em;
+    margin-left: 0em;
+    margin-bottom: 0em;
+}
+
+dl {
+    margin-bottom: 15px;
+}
+
+dd > :first-child {
+    margin-top: 0px;
+}
+
+dd ul, dd table {
+    margin-bottom: 10px;
+}
+
+dd {
+    margin-top: 3px;
+    margin-bottom: 10px;
+    margin-left: 30px;
+}
+
+.sig dd {
+    margin-top: 0px;
+    margin-bottom: 0px;
+}
+
+.sig dl {
+    margin-top: 0px;
+    margin-bottom: 0px;
+}
+
+dl > dd:last-child,
+dl > dd:last-child > :last-child {
+    margin-bottom: 0;
+}
+
+dt:target, span.highlighted {
+    background-color: #fbe54e;
+}
+
+rect.highlighted {
+    fill: #fbe54e;
+}
+
+dl.glossary dt {
+    font-weight: bold;
+    font-size: 1.1em;
+}
+
+.versionmodified {
+    font-style: italic;
+}
+
+.system-message {
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\ No newline at end of file
diff --git a/_static/dark_mode_css/custom.css b/_static/dark_mode_css/custom.css
new file mode 100644
index 00000000..989c2ada
--- /dev/null
+++ b/_static/dark_mode_css/custom.css
@@ -0,0 +1,77 @@
+.wy-side-nav-search input[type='text'] {
+  border-radius: 3px;
+}
+
+input[type='color'],
+input[type='date'],
+input[type='datetime-local'],
+input[type='datetime'],
+input[type='email'],
+input[type='month'],
+input[type='number'],
+input[type='password'],
+input[type='search'],
+input[type='tel'],
+input[type='text'],
+input[type='time'],
+input[type='url'],
+input[type='week'] {
+  box-shadow: none;
+}
+
+.theme-switcher {
+  border-radius: 50%;
+  position: fixed;
+  right: 1.6em;
+  bottom: 1.4em;
+  z-index: 3;
+  border: none;
+  height: 2.2em;
+  width: 2.2em;
+  background-color: #fcfcfc;
+  font-size: 20px;
+  -webkit-box-shadow: 0px 3px 14px 4px rgba(0, 0, 0, 0.62);
+  box-shadow: 0px 3px 14px 4px rgba(0, 0, 0, 0.62);
+  color: #404040;
+  transition: all 0.3s ease-in-out;
+}
+
+.wy-nav-content a,
+.wy-nav-content a:visited {
+  color: #3091d1;
+}
+
+body,
+.wy-nav-content-wrap,
+.wy-nav-content,
+.section,
+.highlight,
+.rst-content div[class^='highlight'],
+.wy-nav-content a,
+.btn-neutral,
+.btn,
+footer,
+.wy-nav-side,
+.wy-menu-vertical li,
+.wy-menu-vertical a,
+.wy-side-nav-search .wy-dropdown,
+.wy-side-nav-search a,
+.wy-side-nav-search input,
+html.writer-html4 .rst-content dl:not(.docutils) > dt,
+html.writer-html5
+  .rst-content
+  dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.glossary):not(.simple)
+  > dt,
+.rst-content code,
+.rst-content tt,
+html.writer-html4 .rst-content dl:not(.docutils) dl:not(.field-list) > dt,
+html.writer-html5
+  .rst-content
+  dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.glossary):not(.simple)
+  dl:not(.field-list)
+  > dt,
+code,
+.rst-content code.xref,
+.rst-content tt.xref {
+  transition: all 0.2s ease-in-out;
+}
diff --git a/_static/dark_mode_css/dark.css b/_static/dark_mode_css/dark.css
new file mode 100644
index 00000000..e863889c
--- /dev/null
+++ b/_static/dark_mode_css/dark.css
@@ -0,0 +1,520 @@
+:root {
+  --dark-text-color: #c1c1c1;
+  --dark-link-color: #249ee8;
+}
+
+html[data-theme="dark"] body {
+  color: #bfbfbf;
+}
+
+html[data-theme="dark"] .wy-nav-content-wrap {
+  background-color: #101010;
+}
+
+html[data-theme="dark"] .wy-nav-content {
+  background-color: #141414;
+}
+
+html[data-theme="dark"] .section {
+  color: var(--dark-text-color);
+}
+
+html[data-theme="dark"] .highlight {
+  background-color: #17181c;
+}
+
+html[data-theme="dark"] .highlight .nn {
+  color: var(--dark-text-color);
+}
+
+html[data-theme="dark"] .highlight .nb {
+  color: #8bb8df;
+}
+
+html[data-theme="dark"] .highlight .nv {
+  color: #40ffff;
+}
+
+html[data-theme="dark"] .highlight .kn,
+html[data-theme="dark"] .highlight .kc,
+html[data-theme="dark"] .highlight .k {
+  color: #41c2ea;
+}
+
+html[data-theme="dark"] .highlight .s1,
+html[data-theme="dark"] .highlight .s2 {
+  color: #b3e87f;
+}
+
+html[data-theme="dark"] .highlight .nt {
+  color: #ccb350;
+}
+
+html[data-theme="dark"] .highlight .c1 {
+  color: #686868;
+}
+
+html[data-theme="dark"] .highlight .hll {
+  background-color: #002c4d;
+}
+
+html[data-theme="dark"] .rst-content div[class^="highlight"] {
+  border-color: #1a1a1a;
+}
+
+html[data-theme="dark"] .wy-nav-content a,
+html[data-theme="dark"] .wy-nav-content a:visited {
+  color: var(--dark-link-color);
+}
+
+html[data-theme="dark"] .btn-neutral {
+  background-color: #17181c !important;
+}
+
+html[data-theme="dark"] .btn-neutral:hover {
+  background-color: #101114 !important;
+}
+
+html[data-theme="dark"] .btn-neutral:visited {
+  color: #c1c1c1 !important;
+}
+
+html[data-theme="dark"] .btn {
+  box-shadow: none;
+}
+
+html[data-theme="dark"] footer {
+  color: #bdbdbd;
+}
+
+html[data-theme="dark"] .wy-nav-side {
+  background-color: #0d0d0d;
+}
+
+html[data-theme="dark"] .wy-menu-vertical li.current {
+  background-color: #141414;
+}
+
+html[data-theme="dark"] .wy-menu-vertical li.current > a,
+html[data-theme="dark"] .wy-menu-vertical li.on a {
+  background-color: #141415;
+  color: var(--dark-text-color);
+}
+
+html[data-theme="dark"] .wy-menu-vertical li.toctree-l1.current > a,
+html[data-theme="dark"] .wy-menu-vertical li.current a {
+  border-color: #0b0c0d;
+}
+
+html[data-theme="dark"] .wy-menu-vertical li.current a {
+  color: #bbb;
+}
+
+html[data-theme="dark"] .wy-menu-vertical li.current a:hover {
+  background-color: #222;
+}
+
+html[data-theme="dark"] .wy-menu-vertical a:hover,
+html[data-theme="dark"] .wy-menu-vertical li.current > a:hover,
+html[data-theme="dark"] .wy-menu-vertical li.on a:hover {
+  background-color: #1e1e1e;
+}
+
+html[data-theme="dark"] .wy-menu-vertical li.toctree-l2.current > a,
+html[data-theme="dark"]
+  .wy-menu-vertical
+  li.toctree-l2.current
+  li.toctree-l3
+  > a {
+  background-color: #18181a;
+}
+
+html[data-theme="dark"] .wy-side-nav-search {
+  background-color: #0b152d;
+}
+
+html[data-theme="dark"] .wy-side-nav-search .wy-dropdown > a,
+html[data-theme="dark"] .wy-side-nav-search > a {
+  color: #ddd;
+}
+
+html[data-theme="dark"] .wy-side-nav-search input[type="text"] {
+  border-color: #111;
+  background-color: #141414;
+  color: var(--dark-text-color);
+}
+
+html[data-theme="dark"] .theme-switcher {
+  background-color: #0b0c0d;
+  color: var(--dark-text-color);
+}
+
+html[data-theme="dark"].writer-html4 .rst-content dl:not(.docutils) > dt,
+html[data-theme="dark"].writer-html5
+  .rst-content
+  dl[class]:not(.option-list):not(.field-list):not(.footnote):not(
+    .glossary
+  ):not(.simple)
+  > dt {
+  background-color: #0b0b0b;
+  color: #007dce;
+  border-color: #282828;
+}
+
+html[data-theme="dark"] .rst-content code,
+html[data-theme="dark"] .rst-content tt {
+  color: var(--dark-text-color);
+}
+
+html[data-theme="dark"].writer-html4
+  .rst-content
+  dl:not(.docutils)
+  dl:not(.field-list)
+  > dt,
+html[data-theme="dark"].writer-html5
+  .rst-content
+  dl[class]:not(.option-list):not(.field-list):not(.footnote):not(
+    .glossary
+  ):not(.simple)
+  dl:not(.field-list)
+  > dt {
+  background-color: #0f0f0f;
+  color: #959595;
+  border-color: #2b2b2b;
+}
+
+html[data-theme="dark"] .rst-content code,
+html[data-theme="dark"] .rst-content tt,
+html[data-theme="dark"] code {
+  background-color: #2d2d2d;
+  border-color: #1c1c1c;
+}
+
+html[data-theme="dark"] .rst-content code.xref,
+html[data-theme="dark"] .rst-content tt.xref,
+html[data-theme="dark"] a .rst-content code,
+html[data-theme="dark"] a .rst-content tt {
+  color: #cecece;
+}
+
+html[data-theme="dark"] .rst-content .hint,
+html[data-theme="dark"] .rst-content .important,
+html[data-theme="dark"] .rst-content .tip,
+html[data-theme="dark"] .rst-content .wy-alert-success.admonition,
+html[data-theme="dark"] .rst-content .wy-alert-success.admonition-todo,
+html[data-theme="dark"] .rst-content .wy-alert-success.attention,
+html[data-theme="dark"] .rst-content .wy-alert-success.caution,
+html[data-theme="dark"] .rst-content .wy-alert-success.danger,
+html[data-theme="dark"] .rst-content .wy-alert-success.error,
+html[data-theme="dark"] .rst-content .wy-alert-success.note,
+html[data-theme="dark"] .rst-content .wy-alert-success.seealso,
+html[data-theme="dark"] .rst-content .wy-alert-success.warning,
+html[data-theme="dark"] .wy-alert.wy-alert-success {
+  background-color: #00392e;
+}
+
+html[data-theme="dark"] .rst-content .hint .admonition-title,
+html[data-theme="dark"] .rst-content .hint .wy-alert-title,
+html[data-theme="dark"] .rst-content .important .admonition-title,
+html[data-theme="dark"] .rst-content .important .wy-alert-title,
+html[data-theme="dark"] .rst-content .tip .admonition-title,
+html[data-theme="dark"] .rst-content .tip .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-success.admonition-todo
+  .admonition-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-success.admonition-todo
+  .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-success.admonition
+  .admonition-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-success.admonition
+  .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-success.attention
+  .admonition-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-success.attention
+  .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-success.caution
+  .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-success.caution .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-success.danger .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-success.danger .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-success.error .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-success.error .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-success.note .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-success.note .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-success.seealso
+  .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-success.seealso .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-success.warning
+  .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-success.warning .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert.wy-alert-success
+  .admonition-title,
+html[data-theme="dark"]
+  .wy-alert.wy-alert-success
+  .rst-content
+  .admonition-title,
+html[data-theme="dark"] .wy-alert.wy-alert-success .wy-alert-title {
+  background-color: #006a56;
+}
+
+html[data-theme="dark"] .rst-content .admonition,
+html[data-theme="dark"] .rst-content .note,
+html[data-theme="dark"] .rst-content .seealso,
+html[data-theme="dark"] .rst-content .wy-alert-info.admonition,
+html[data-theme="dark"] .rst-content .wy-alert-info.admonition-todo,
+html[data-theme="dark"] .rst-content .wy-alert-info.attention,
+html[data-theme="dark"] .rst-content .wy-alert-info.caution,
+html[data-theme="dark"] .rst-content .wy-alert-info.danger,
+html[data-theme="dark"] .rst-content .wy-alert-info.error,
+html[data-theme="dark"] .rst-content .wy-alert-info.hint,
+html[data-theme="dark"] .rst-content .wy-alert-info.important,
+html[data-theme="dark"] .rst-content .wy-alert-info.tip,
+html[data-theme="dark"] .rst-content .wy-alert-info.warning,
+html[data-theme="dark"] .wy-alert.wy-alert-info {
+  background-color: #002c4d;
+}
+
+html[data-theme="dark"] .rst-content .admonition .admonition-title,
+html[data-theme="dark"] .rst-content .note .admonition-title,
+html[data-theme="dark"] .rst-content .note .wy-alert-title,
+html[data-theme="dark"] .rst-content .seealso .admonition-title,
+html[data-theme="dark"] .rst-content .seealso .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-info.admonition-todo
+  .admonition-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-info.admonition-todo
+  .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-info.admonition
+  .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.admonition .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.attention .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.attention .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.caution .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.caution .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.danger .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.danger .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.error .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.error .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.hint .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.hint .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.important .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.important .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.tip .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.tip .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.warning .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-info.warning .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert.wy-alert-info .admonition-title,
+html[data-theme="dark"] .wy-alert.wy-alert-info .rst-content .admonition-title,
+html[data-theme="dark"] .wy-alert.wy-alert-info .wy-alert-title {
+  background-color: #004a7b;
+}
+
+html[data-theme="dark"] .rst-content .admonition-todo,
+html[data-theme="dark"] .rst-content .attention,
+html[data-theme="dark"] .rst-content .caution,
+html[data-theme="dark"] .rst-content .warning,
+html[data-theme="dark"] .rst-content .wy-alert-warning.admonition,
+html[data-theme="dark"] .rst-content .wy-alert-warning.danger,
+html[data-theme="dark"] .rst-content .wy-alert-warning.error,
+html[data-theme="dark"] .rst-content .wy-alert-warning.hint,
+html[data-theme="dark"] .rst-content .wy-alert-warning.important,
+html[data-theme="dark"] .rst-content .wy-alert-warning.note,
+html[data-theme="dark"] .rst-content .wy-alert-warning.seealso,
+html[data-theme="dark"] .rst-content .wy-alert-warning.tip,
+html[data-theme="dark"] .wy-alert.wy-alert-warning {
+  background-color: #533500;
+}
+
+html[data-theme="dark"] .rst-content .admonition-todo .admonition-title,
+html[data-theme="dark"] .rst-content .admonition-todo .wy-alert-title,
+html[data-theme="dark"] .rst-content .attention .admonition-title,
+html[data-theme="dark"] .rst-content .attention .wy-alert-title,
+html[data-theme="dark"] .rst-content .caution .admonition-title,
+html[data-theme="dark"] .rst-content .caution .wy-alert-title,
+html[data-theme="dark"] .rst-content .warning .admonition-title,
+html[data-theme="dark"] .rst-content .warning .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-warning.admonition
+  .admonition-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-warning.admonition
+  .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.danger .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.danger .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.error .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.error .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.hint .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.hint .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-warning.important
+  .admonition-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-warning.important
+  .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.note .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.note .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-warning.seealso
+  .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.seealso .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.tip .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-warning.tip .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert.wy-alert-warning
+  .admonition-title,
+html[data-theme="dark"]
+  .wy-alert.wy-alert-warning
+  .rst-content
+  .admonition-title,
+html[data-theme="dark"] .wy-alert.wy-alert-warning .wy-alert-title {
+  background-color: #803b00;
+}
+
+html[data-theme="dark"] .rst-content .danger,
+html[data-theme="dark"] .rst-content .error,
+html[data-theme="dark"] .rst-content .wy-alert-danger.admonition,
+html[data-theme="dark"] .rst-content .wy-alert-danger.admonition-todo,
+html[data-theme="dark"] .rst-content .wy-alert-danger.attention,
+html[data-theme="dark"] .rst-content .wy-alert-danger.caution,
+html[data-theme="dark"] .rst-content .wy-alert-danger.hint,
+html[data-theme="dark"] .rst-content .wy-alert-danger.important,
+html[data-theme="dark"] .rst-content .wy-alert-danger.note,
+html[data-theme="dark"] .rst-content .wy-alert-danger.seealso,
+html[data-theme="dark"] .rst-content .wy-alert-danger.tip,
+html[data-theme="dark"] .rst-content .wy-alert-danger.warning,
+html[data-theme="dark"] .wy-alert.wy-alert-danger {
+  background-color: #82231a;
+}
+
+html[data-theme="dark"] .rst-content .danger .admonition-title,
+html[data-theme="dark"] .rst-content .danger .wy-alert-title,
+html[data-theme="dark"] .rst-content .error .admonition-title,
+html[data-theme="dark"] .rst-content .error .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-danger.admonition-todo
+  .admonition-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-danger.admonition-todo
+  .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-danger.admonition
+  .admonition-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-danger.admonition
+  .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-danger.attention
+  .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.attention .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.caution .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.caution .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.hint .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.hint .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert-danger.important
+  .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.important .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.note .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.note .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.seealso .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.seealso .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.tip .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.tip .wy-alert-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.warning .admonition-title,
+html[data-theme="dark"] .rst-content .wy-alert-danger.warning .wy-alert-title,
+html[data-theme="dark"]
+  .rst-content
+  .wy-alert.wy-alert-danger
+  .admonition-title,
+html[data-theme="dark"]
+  .wy-alert.wy-alert-danger
+  .rst-content
+  .admonition-title,
+html[data-theme="dark"] .wy-alert.wy-alert-danger .wy-alert-title {
+  background-color: #b9372b;
+}
+
+html[data-theme="dark"] .wy-nav-top {
+  background-color: #0b152d;
+}
+
+html[data-theme="dark"] .rst-content table.docutils thead,
+html[data-theme="dark"] .rst-content table.field-list thead,
+html[data-theme="dark"] .wy-table thead {
+  color: var(--dark-text-color);
+}
+
+html[data-theme="dark"]
+  .rst-content
+  table.docutils:not(.field-list)
+  tr:nth-child(2n-1)
+  td,
+html[data-theme="dark"] .wy-table-backed,
+html[data-theme="dark"] html[data-theme="dark"] .wy-table-odd td,
+html[data-theme="dark"] .wy-table-striped tr:nth-child(2n-1) td {
+  background-color: #181818;
+}
+
+html[data-theme="dark"] .rst-content table.docutils td,
+html[data-theme="dark"] .wy-table-bordered-all td,
+html[data-theme="dark"].writer-html5 .rst-content table.docutils th,
+html[data-theme="dark"] .rst-content table.docutils,
+html[data-theme="dark"] .wy-table-bordered-all {
+  border-color: #262626;
+}
+
+html[data-theme="dark"] .rst-content table.docutils caption,
+html[data-theme="dark"] .rst-content table.field-list caption,
+html[data-theme="dark"] .wy-table caption {
+  color: var(--dark-text-color);
+}
+
+html[data-theme="dark"] .wy-menu-vertical li.toctree-l3.current > a,
+html[data-theme="dark"]
+  .wy-menu-vertical
+  li.toctree-l3.current
+  li.toctree-l4
+  > a {
+  background-color: #18181a;
+}
+
+html[data-theme="dark"] .guilabel {
+  background-color: #343434;
+  border-color: #4d4d4d;
+}
diff --git a/_static/dark_mode_css/general.css b/_static/dark_mode_css/general.css
new file mode 100644
index 00000000..aa614f81
--- /dev/null
+++ b/_static/dark_mode_css/general.css
@@ -0,0 +1,68 @@
+input[type='color'],
+input[type='date'],
+input[type='datetime-local'],
+input[type='datetime'],
+input[type='email'],
+input[type='month'],
+input[type='number'],
+input[type='password'],
+input[type='search'],
+input[type='tel'],
+input[type='text'],
+input[type='time'],
+input[type='url'],
+input[type='week'] {
+  box-shadow: none;
+}
+
+.theme-switcher {
+  border-radius: 50%;
+  position: fixed;
+  right: 1.6em;
+  bottom: 1.4em;
+  z-index: 3;
+  border: none;
+  height: 2.2em;
+  width: 2.2em;
+  background-color: #fcfcfc;
+  font-size: 20px;
+  -webkit-box-shadow: 0px 3px 14px 4px rgba(0, 0, 0, 0.62);
+  box-shadow: 0px 3px 14px 4px rgba(0, 0, 0, 0.62);
+  color: #404040;
+  transition: all 0.3s ease-in-out;
+}
+
+body,
+.wy-nav-content-wrap,
+.wy-nav-content,
+.section,
+.highlight,
+.rst-content div[class^='highlight'],
+.wy-nav-content a,
+.btn-neutral,
+.btn,
+footer,
+.wy-nav-side,
+.wy-menu-vertical li,
+.wy-menu-vertical a,
+.wy-side-nav-search .wy-dropdown,
+.wy-side-nav-search a,
+.wy-side-nav-search input,
+html.writer-html4 .rst-content dl:not(.docutils) > dt,
+html.writer-html5
+  .rst-content
+  dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.glossary):not(.simple)
+  > dt,
+.rst-content code,
+.rst-content tt,
+html.writer-html4 .rst-content dl:not(.docutils) dl:not(.field-list) > dt,
+html.writer-html5
+  .rst-content
+  dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.glossary):not(.simple)
+  dl:not(.field-list)
+  > dt,
+code,
+.rst-content code.xref,
+.rst-content tt.xref {
+  transition: all 0.2s ease-in-out;
+}
diff --git a/_static/dark_mode_js/default_dark.js b/_static/dark_mode_js/default_dark.js
new file mode 100644
index 00000000..ea63e072
--- /dev/null
+++ b/_static/dark_mode_js/default_dark.js
@@ -0,0 +1,13 @@
+const loadTheme = () => {
+  let theme = localStorage.getItem('theme');
+
+  if (theme !== null) {
+    if (theme === 'dark')
+      document.documentElement.setAttribute('data-theme', 'dark');
+  } else {
+    localStorage.setItem('theme', 'dark');
+    document.documentElement.setAttribute('data-theme', 'dark');
+  }
+};
+
+loadTheme();
diff --git a/_static/dark_mode_js/default_light.js b/_static/dark_mode_js/default_light.js
new file mode 100644
index 00000000..2b19f92e
--- /dev/null
+++ b/_static/dark_mode_js/default_light.js
@@ -0,0 +1,13 @@
+const loadTheme = () => {
+  let theme = localStorage.getItem('theme');
+
+  if (theme !== null) {
+    if (theme === 'dark')
+      document.documentElement.setAttribute('data-theme', 'dark');
+  } else {
+    localStorage.setItem('theme', 'light');
+    document.documentElement.setAttribute('data-theme', 'light');
+  }
+};
+
+loadTheme();
diff --git a/_static/dark_mode_js/theme_switcher.js b/_static/dark_mode_js/theme_switcher.js
new file mode 100644
index 00000000..8e260552
--- /dev/null
+++ b/_static/dark_mode_js/theme_switcher.js
@@ -0,0 +1,39 @@
+const createThemeSwitcher = () => {
+  let btn = document.createElement('BUTTON');
+  btn.className = 'theme-switcher';
+  btn.id = 'themeSwitcher';
+  btn.innerHTML =
+    '<i id=themeMoon class="fa fa-moon-o"></i><i id=themeSun class="fa fa-sun-o"></i>';
+  document.body.appendChild(btn);
+
+  if (localStorage.getItem('theme') === 'dark') $('#themeMoon').hide(0);
+  else $('#themeSun').hide(0);
+};
+
+$(document).ready(() => {
+  createThemeSwitcher();
+  $('#themeSwitcher').click(switchTheme);
+
+  $('footer').html(
+    $('footer').html() +
+      '<a href="https://github.com/MrDogeBro/sphinx_rtd_dark_mode">Dark theme</a> provided by <a href="http://mrdogebro.com">MrDogeBro</a>.'
+  );
+});
+
+const switchTheme = () => {
+  if (localStorage.getItem('theme') === 'dark') {
+    localStorage.setItem('theme', 'light');
+    document.documentElement.setAttribute('data-theme', 'light');
+
+    $('#themeSun').fadeOut(200, () => {
+      $('#themeMoon').fadeIn(200);
+    });
+  } else {
+    localStorage.setItem('theme', 'dark');
+    document.documentElement.setAttribute('data-theme', 'dark');
+
+    $('#themeMoon').fadeOut(200, () => {
+      $('#themeSun').fadeIn(200);
+    });
+  }
+};
diff --git a/_static/doctools.js b/_static/doctools.js
new file mode 100644
index 00000000..d06a71d7
--- /dev/null
+++ b/_static/doctools.js
@@ -0,0 +1,156 @@
+/*
+ * doctools.js
+ * ~~~~~~~~~~~
+ *
+ * Base JavaScript utilities for all Sphinx HTML documentation.
+ *
+ * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+"use strict";
+
+const BLACKLISTED_KEY_CONTROL_ELEMENTS = new Set([
+  "TEXTAREA",
+  "INPUT",
+  "SELECT",
+  "BUTTON",
+]);
+
+const _ready = (callback) => {
+  if (document.readyState !== "loading") {
+    callback();
+  } else {
+    document.addEventListener("DOMContentLoaded", callback);
+  }
+};
+
+/**
+ * Small JavaScript module for the documentation.
+ */
+const Documentation = {
+  init: () => {
+    Documentation.initDomainIndexTable();
+    Documentation.initOnKeyListeners();
+  },
+
+  /**
+   * i18n support
+   */
+  TRANSLATIONS: {},
+  PLURAL_EXPR: (n) => (n === 1 ? 0 : 1),
+  LOCALE: "unknown",
+
+  // gettext and ngettext don't access this so that the functions
+  // can safely bound to a different name (_ = Documentation.gettext)
+  gettext: (string) => {
+    const translated = Documentation.TRANSLATIONS[string];
+    switch (typeof translated) {
+      case "undefined":
+        return string; // no translation
+      case "string":
+        return translated; // translation exists
+      default:
+        return translated[0]; // (singular, plural) translation tuple exists
+    }
+  },
+
+  ngettext: (singular, plural, n) => {
+    const translated = Documentation.TRANSLATIONS[singular];
+    if (typeof translated !== "undefined")
+      return translated[Documentation.PLURAL_EXPR(n)];
+    return n === 1 ? singular : plural;
+  },
+
+  addTranslations: (catalog) => {
+    Object.assign(Documentation.TRANSLATIONS, catalog.messages);
+    Documentation.PLURAL_EXPR = new Function(
+      "n",
+      `return (${catalog.plural_expr})`
+    );
+    Documentation.LOCALE = catalog.locale;
+  },
+
+  /**
+   * helper function to focus on search bar
+   */
+  focusSearchBar: () => {
+    document.querySelectorAll("input[name=q]")[0]?.focus();
+  },
+
+  /**
+   * Initialise the domain index toggle buttons
+   */
+  initDomainIndexTable: () => {
+    const toggler = (el) => {
+      const idNumber = el.id.substr(7);
+      const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`);
+      if (el.src.substr(-9) === "minus.png") {
+        el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`;
+        toggledRows.forEach((el) => (el.style.display = "none"));
+      } else {
+        el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`;
+        toggledRows.forEach((el) => (el.style.display = ""));
+      }
+    };
+
+    const togglerElements = document.querySelectorAll("img.toggler");
+    togglerElements.forEach((el) =>
+      el.addEventListener("click", (event) => toggler(event.currentTarget))
+    );
+    togglerElements.forEach((el) => (el.style.display = ""));
+    if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler);
+  },
+
+  initOnKeyListeners: () => {
+    // only install a listener if it is really needed
+    if (
+      !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS &&
+      !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS
+    )
+      return;
+
+    document.addEventListener("keydown", (event) => {
+      // bail for input elements
+      if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return;
+      // bail with special keys
+      if (event.altKey || event.ctrlKey || event.metaKey) return;
+
+      if (!event.shiftKey) {
+        switch (event.key) {
+          case "ArrowLeft":
+            if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break;
+
+            const prevLink = document.querySelector('link[rel="prev"]');
+            if (prevLink && prevLink.href) {
+              window.location.href = prevLink.href;
+              event.preventDefault();
+            }
+            break;
+          case "ArrowRight":
+            if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break;
+
+            const nextLink = document.querySelector('link[rel="next"]');
+            if (nextLink && nextLink.href) {
+              window.location.href = nextLink.href;
+              event.preventDefault();
+            }
+            break;
+        }
+      }
+
+      // some keyboard layouts may need Shift to get /
+      switch (event.key) {
+        case "/":
+          if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break;
+          Documentation.focusSearchBar();
+          event.preventDefault();
+      }
+    });
+  },
+};
+
+// quick alias for translations
+const _ = Documentation.gettext;
+
+_ready(Documentation.init);
diff --git a/_static/documentation_options.js b/_static/documentation_options.js
new file mode 100644
index 00000000..7e4c114f
--- /dev/null
+++ b/_static/documentation_options.js
@@ -0,0 +1,13 @@
+const DOCUMENTATION_OPTIONS = {
+    VERSION: '',
+    LANGUAGE: 'en',
+    COLLAPSE_INDEX: false,
+    BUILDER: 'html',
+    FILE_SUFFIX: '.html',
+    LINK_SUFFIX: '.html',
+    HAS_SOURCE: true,
+    SOURCELINK_SUFFIX: '.txt',
+    NAVIGATION_WITH_KEYS: false,
+    SHOW_SEARCH_SUMMARY: true,
+    ENABLE_SEARCH_SHORTCUTS: true,
+};
\ No newline at end of file
diff --git a/_static/file.png b/_static/file.png
new file mode 100644
index 00000000..a858a410
Binary files /dev/null and b/_static/file.png differ
diff --git a/_static/jquery.js b/_static/jquery.js
new file mode 100644
index 00000000..c4c6022f
--- /dev/null
+++ b/_static/jquery.js
@@ -0,0 +1,2 @@
+/*! jQuery v3.6.0 | (c) OpenJS Foundation and other contributors | jquery.org/license */
+!function(e,t){"use strict";"object"==typeof module&&"object"==typeof module.exports?module.exports=e.document?t(e,!0):function(e){if(!e.document)throw new Error("jQuery requires a window with a document");return t(e)}:t(e)}("undefined"!=typeof window?window:this,function(C,e){"use strict";var t=[],r=Object.getPrototypeOf,s=t.slice,g=t.flat?function(e){return t.flat.call(e)}:function(e){return t.concat.apply([],e)},u=t.push,i=t.indexOf,n={},o=n.toString,v=n.hasOwnProperty,a=v.toString,l=a.call(Object),y={},m=function(e){return"function"==typeof e&&"number"!=typeof e.nodeType&&"function"!=typeof e.item},x=function(e){return null!=e&&e===e.window},E=C.document,c={type:!0,src:!0,nonce:!0,noModule:!0};function b(e,t,n){var r,i,o=(n=n||E).createElement("script");if(o.text=e,t)for(r in c)(i=t[r]||t.getAttribute&&t.getAttribute(r))&&o.setAttribute(r,i);n.head.appendChild(o).parentNode.removeChild(o)}function w(e){return null==e?e+"":"object"==typeof e||"function"==typeof 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new file mode 100644
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+!function(a,b){function c(a,b){var c=a.createElement("p"),d=a.getElementsByTagName("head")[0]||a.documentElement;return c.innerHTML="x<style>"+b+"</style>",d.insertBefore(c.lastChild,d.firstChild)}function d(){var a=t.elements;return"string"==typeof a?a.split(" "):a}function e(a,b){var c=t.elements;"string"!=typeof c&&(c=c.join(" ")),"string"!=typeof a&&(a=a.join(" ")),t.elements=c+" "+a,j(b)}function f(a){var b=s[a[q]];return b||(b={},r++,a[q]=r,s[r]=b),b}function g(a,c,d){if(c||(c=b),l)return c.createElement(a);d||(d=f(c));var e;return e=d.cache[a]?d.cache[a].cloneNode():p.test(a)?(d.cache[a]=d.createElem(a)).cloneNode():d.createElem(a),!e.canHaveChildren||o.test(a)||e.tagUrn?e:d.frag.appendChild(e)}function h(a,c){if(a||(a=b),l)return a.createDocumentFragment();c=c||f(a);for(var e=c.frag.cloneNode(),g=0,h=d(),i=h.length;i>g;g++)e.createElement(h[g]);return e}function i(a,b){b.cache||(b.cache={},b.createElem=a.createElement,b.createFrag=a.createDocumentFragment,b.frag=b.createFrag()),a.createElement=function(c){return t.shivMethods?g(c,a,b):b.createElem(c)},a.createDocumentFragment=Function("h,f","return function(){var n=f.cloneNode(),c=n.createElement;h.shivMethods&&("+d().join().replace(/[\w\-:]+/g,function(a){return b.createElem(a),b.frag.createElement(a),'c("'+a+'")'})+");return n}")(t,b.frag)}function j(a){a||(a=b);var d=f(a);return!t.shivCSS||k||d.hasCSS||(d.hasCSS=!!c(a,"article,aside,dialog,figcaption,figure,footer,header,hgroup,main,nav,section{display:block}mark{background:#FF0;color:#000}template{display:none}")),l||i(a,d),a}var k,l,m="3.7.3-pre",n=a.html5||{},o=/^<|^(?:button|map|select|textarea|object|iframe|option|optgroup)$/i,p=/^(?:a|b|code|div|fieldset|h1|h2|h3|h4|h5|h6|i|label|li|ol|p|q|span|strong|style|table|tbody|td|th|tr|ul)$/i,q="_html5shiv",r=0,s={};!function(){try{var a=b.createElement("a");a.innerHTML="<xyz></xyz>",k="hidden"in a,l=1==a.childNodes.length||function(){b.createElement("a");var a=b.createDocumentFragment();return"undefined"==typeof a.cloneNode||"undefined"==typeof a.createDocumentFragment||"undefined"==typeof a.createElement}()}catch(c){k=!0,l=!0}}();var t={elements:n.elements||"abbr article aside audio bdi canvas data datalist details dialog figcaption figure footer header hgroup main mark meter nav output picture progress section summary template time video",version:m,shivCSS:n.shivCSS!==!1,supportsUnknownElements:l,shivMethods:n.shivMethods!==!1,type:"default",shivDocument:j,createElement:g,createDocumentFragment:h,addElements:e};a.html5=t,j(b),"object"==typeof module&&module.exports&&(module.exports=t)}("undefined"!=typeof window?window:this,document);
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diff --git a/_static/js/theme.js b/_static/js/theme.js
new file mode 100644
index 00000000..1fddb6ee
--- /dev/null
+++ b/_static/js/theme.js
@@ -0,0 +1 @@
+!function(n){var e={};function t(i){if(e[i])return e[i].exports;var o=e[i]={i:i,l:!1,exports:{}};return n[i].call(o.exports,o,o.exports,t),o.l=!0,o.exports}t.m=n,t.c=e,t.d=function(n,e,i){t.o(n,e)||Object.defineProperty(n,e,{enumerable:!0,get:i})},t.r=function(n){"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(n,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(n,"__esModule",{value:!0})},t.t=function(n,e){if(1&e&&(n=t(n)),8&e)return n;if(4&e&&"object"==typeof n&&n&&n.__esModule)return n;var i=Object.create(null);if(t.r(i),Object.defineProperty(i,"default",{enumerable:!0,value:n}),2&e&&"string"!=typeof n)for(var o in n)t.d(i,o,function(e){return n[e]}.bind(null,o));return i},t.n=function(n){var e=n&&n.__esModule?function(){return n.default}:function(){return n};return t.d(e,"a",e),e},t.o=function(n,e){return Object.prototype.hasOwnProperty.call(n,e)},t.p="",t(t.s=0)}([function(n,e,t){t(1),n.exports=t(3)},function(n,e,t){(function(){var e="undefined"!=typeof window?window.jQuery:t(2);n.exports.ThemeNav={navBar:null,win:null,winScroll:!1,winResize:!1,linkScroll:!1,winPosition:0,winHeight:null,docHeight:null,isRunning:!1,enable:function(n){var t=this;void 0===n&&(n=!0),t.isRunning||(t.isRunning=!0,e((function(e){t.init(e),t.reset(),t.win.on("hashchange",t.reset),n&&t.win.on("scroll",(function(){t.linkScroll||t.winScroll||(t.winScroll=!0,requestAnimationFrame((function(){t.onScroll()})))})),t.win.on("resize",(function(){t.winResize||(t.winResize=!0,requestAnimationFrame((function(){t.onResize()})))})),t.onResize()})))},enableSticky:function(){this.enable(!0)},init:function(n){n(document);var e=this;this.navBar=n("div.wy-side-scroll:first"),this.win=n(window),n(document).on("click","[data-toggle='wy-nav-top']",(function(){n("[data-toggle='wy-nav-shift']").toggleClass("shift"),n("[data-toggle='rst-versions']").toggleClass("shift")})).on("click",".wy-menu-vertical .current ul li a",(function(){var 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\ No newline at end of file
diff --git a/_static/language_data.js b/_static/language_data.js
new file mode 100644
index 00000000..250f5665
--- /dev/null
+++ b/_static/language_data.js
@@ -0,0 +1,199 @@
+/*
+ * language_data.js
+ * ~~~~~~~~~~~~~~~~
+ *
+ * This script contains the language-specific data used by searchtools.js,
+ * namely the list of stopwords, stemmer, scorer and splitter.
+ *
+ * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+
+var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"];
+
+
+/* Non-minified version is copied as a separate JS file, is available */
+
+/**
+ * Porter Stemmer
+ */
+var Stemmer = function() {
+
+  var step2list = {
+    ational: 'ate',
+    tional: 'tion',
+    enci: 'ence',
+    anci: 'ance',
+    izer: 'ize',
+    bli: 'ble',
+    alli: 'al',
+    entli: 'ent',
+    eli: 'e',
+    ousli: 'ous',
+    ization: 'ize',
+    ation: 'ate',
+    ator: 'ate',
+    alism: 'al',
+    iveness: 'ive',
+    fulness: 'ful',
+    ousness: 'ous',
+    aliti: 'al',
+    iviti: 'ive',
+    biliti: 'ble',
+    logi: 'log'
+  };
+
+  var step3list = {
+    icate: 'ic',
+    ative: '',
+    alize: 'al',
+    iciti: 'ic',
+    ical: 'ic',
+    ful: '',
+    ness: ''
+  };
+
+  var c = "[^aeiou]";          // consonant
+  var v = "[aeiouy]";          // vowel
+  var C = c + "[^aeiouy]*";    // consonant sequence
+  var V = v + "[aeiou]*";      // vowel sequence
+
+  var mgr0 = "^(" + C + ")?" + V + C;                      // [C]VC... is m>0
+  var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$";    // [C]VC[V] is m=1
+  var mgr1 = "^(" + C + ")?" + V + C + V + C;              // [C]VCVC... is m>1
+  var s_v   = "^(" + C + ")?" + v;                         // vowel in stem
+
+  this.stemWord = function (w) {
+    var stem;
+    var suffix;
+    var firstch;
+    var origword = w;
+
+    if (w.length < 3)
+      return w;
+
+    var re;
+    var re2;
+    var re3;
+    var re4;
+
+    firstch = w.substr(0,1);
+    if (firstch == "y")
+      w = firstch.toUpperCase() + w.substr(1);
+
+    // Step 1a
+    re = /^(.+?)(ss|i)es$/;
+    re2 = /^(.+?)([^s])s$/;
+
+    if (re.test(w))
+      w = w.replace(re,"$1$2");
+    else if (re2.test(w))
+      w = w.replace(re2,"$1$2");
+
+    // Step 1b
+    re = /^(.+?)eed$/;
+    re2 = /^(.+?)(ed|ing)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      re = new RegExp(mgr0);
+      if (re.test(fp[1])) {
+        re = /.$/;
+        w = w.replace(re,"");
+      }
+    }
+    else if (re2.test(w)) {
+      var fp = re2.exec(w);
+      stem = fp[1];
+      re2 = new RegExp(s_v);
+      if (re2.test(stem)) {
+        w = stem;
+        re2 = /(at|bl|iz)$/;
+        re3 = new RegExp("([^aeiouylsz])\\1$");
+        re4 = new RegExp("^" + C + v + "[^aeiouwxy]$");
+        if (re2.test(w))
+          w = w + "e";
+        else if (re3.test(w)) {
+          re = /.$/;
+          w = w.replace(re,"");
+        }
+        else if (re4.test(w))
+          w = w + "e";
+      }
+    }
+
+    // Step 1c
+    re = /^(.+?)y$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(s_v);
+      if (re.test(stem))
+        w = stem + "i";
+    }
+
+    // Step 2
+    re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      suffix = fp[2];
+      re = new RegExp(mgr0);
+      if (re.test(stem))
+        w = stem + step2list[suffix];
+    }
+
+    // Step 3
+    re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      suffix = fp[2];
+      re = new RegExp(mgr0);
+      if (re.test(stem))
+        w = stem + step3list[suffix];
+    }
+
+    // Step 4
+    re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
+    re2 = /^(.+?)(s|t)(ion)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(mgr1);
+      if (re.test(stem))
+        w = stem;
+    }
+    else if (re2.test(w)) {
+      var fp = re2.exec(w);
+      stem = fp[1] + fp[2];
+      re2 = new RegExp(mgr1);
+      if (re2.test(stem))
+        w = stem;
+    }
+
+    // Step 5
+    re = /^(.+?)e$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(mgr1);
+      re2 = new RegExp(meq1);
+      re3 = new RegExp("^" + C + v + "[^aeiouwxy]$");
+      if (re.test(stem) || (re2.test(stem) && !(re3.test(stem))))
+        w = stem;
+    }
+    re = /ll$/;
+    re2 = new RegExp(mgr1);
+    if (re.test(w) && re2.test(w)) {
+      re = /.$/;
+      w = w.replace(re,"");
+    }
+
+    // and turn initial Y back to y
+    if (firstch == "y")
+      w = firstch.toLowerCase() + w.substr(1);
+    return w;
+  }
+}
+
diff --git a/_static/minus.png b/_static/minus.png
new file mode 100644
index 00000000..d96755fd
Binary files /dev/null and b/_static/minus.png differ
diff --git a/_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css b/_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css
new file mode 100644
index 00000000..33566310
--- /dev/null
+++ b/_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css
@@ -0,0 +1,2342 @@
+/* Variables */
+:root {
+  --mystnb-source-bg-color: #f7f7f7;
+  --mystnb-stdout-bg-color: #fcfcfc;
+  --mystnb-stderr-bg-color: #fdd;
+  --mystnb-traceback-bg-color: #fcfcfc;
+  --mystnb-source-border-color: #ccc;
+  --mystnb-source-margin-color: green;
+  --mystnb-stdout-border-color: #f7f7f7;
+  --mystnb-stderr-border-color: #f7f7f7;
+  --mystnb-traceback-border-color: #ffd6d6;
+  --mystnb-hide-prompt-opacity: 70%;
+  --mystnb-source-border-radius: .4em;
+  --mystnb-source-border-width: 1px;
+}
+
+/* Whole cell */
+div.container.cell {
+  padding-left: 0;
+  margin-bottom: 1em;
+}
+
+/* Removing all background formatting so we can control at the div level */
+.cell_input div.highlight,
+.cell_output pre,
+.cell_input pre,
+.cell_output .output {
+  border: none;
+  box-shadow: none;
+}
+
+.cell_output .output pre,
+.cell_input pre {
+  margin: 0px;
+}
+
+/* Input cells */
+div.cell div.cell_input,
+div.cell details.above-input>summary {
+  padding-left: 0em;
+  padding-right: 0em;
+  border: var(--mystnb-source-border-width) var(--mystnb-source-border-color) solid;
+  background-color: var(--mystnb-source-bg-color);
+  border-left-color: var(--mystnb-source-margin-color);
+  border-left-width: medium;
+  border-radius: var(--mystnb-source-border-radius);
+}
+
+div.cell_input>div,
+div.cell_output div.output>div.highlight {
+  margin: 0em !important;
+  border: none !important;
+}
+
+/* All cell outputs */
+.cell_output {
+  padding-left: 1em;
+  padding-right: 0em;
+  margin-top: 1em;
+}
+
+/* Text outputs from cells */
+.cell_output .output.text_plain,
+.cell_output .output.traceback,
+.cell_output .output.stream,
+.cell_output .output.stderr {
+  margin-top: 1em;
+  margin-bottom: 0em;
+  box-shadow: none;
+}
+
+.cell_output .output.text_plain,
+.cell_output .output.stream {
+  background: var(--mystnb-stdout-bg-color);
+  border: 1px solid var(--mystnb-stdout-border-color);
+}
+
+.cell_output .output.stderr {
+  background: var(--mystnb-stderr-bg-color);
+  border: 1px solid var(--mystnb-stderr-border-color);
+}
+
+.cell_output .output.traceback {
+  background: var(--mystnb-traceback-bg-color);
+  border: 1px solid var(--mystnb-traceback-border-color);
+}
+
+/* Collapsible cell content */
+div.cell details.above-input div.cell_input {
+  border-top-left-radius: 0;
+  border-top-right-radius: 0;
+  border-top: var(--mystnb-source-border-width) var(--mystnb-source-border-color) dashed;
+}
+
+div.cell div.cell_input.above-output-prompt {
+  border-bottom-left-radius: 0;
+  border-bottom-right-radius: 0;
+}
+
+div.cell details.above-input>summary {
+  border-bottom-left-radius: 0;
+  border-bottom-right-radius: 0;
+  border-bottom: var(--mystnb-source-border-width) var(--mystnb-source-border-color) dashed;
+  padding-left: 1em;
+  margin-bottom: 0;
+}
+
+div.cell details.above-output>summary {
+  background-color: var(--mystnb-source-bg-color);
+  padding-left: 1em;
+  padding-right: 0em;
+  border: var(--mystnb-source-border-width) var(--mystnb-source-border-color) solid;
+  border-radius: var(--mystnb-source-border-radius);
+  border-left-color: var(--mystnb-source-margin-color);
+  border-left-width: medium;
+}
+
+div.cell details.below-input>summary {
+  background-color: var(--mystnb-source-bg-color);
+  padding-left: 1em;
+  padding-right: 0em;
+  border: var(--mystnb-source-border-width) var(--mystnb-source-border-color) solid;
+  border-top: none;
+  border-bottom-left-radius: var(--mystnb-source-border-radius);
+  border-bottom-right-radius: var(--mystnb-source-border-radius);
+  border-left-color: var(--mystnb-source-margin-color);
+  border-left-width: medium;
+}
+
+div.cell details.hide>summary>span {
+  opacity: var(--mystnb-hide-prompt-opacity);
+}
+
+div.cell details.hide[open]>summary>span.collapsed {
+  display: none;
+}
+
+div.cell details.hide:not([open])>summary>span.expanded {
+  display: none;
+}
+
+@keyframes collapsed-fade-in {
+  0% {
+    opacity: 0;
+  }
+
+  100% {
+    opacity: 1;
+  }
+}
+div.cell details.hide[open]>summary~* {
+  -moz-animation: collapsed-fade-in 0.3s ease-in-out;
+  -webkit-animation: collapsed-fade-in 0.3s ease-in-out;
+  animation: collapsed-fade-in 0.3s ease-in-out;
+}
+
+/* Math align to the left */
+.cell_output .MathJax_Display {
+  text-align: left !important;
+}
+
+/* Pandas tables. Pulled from the Jupyter / nbsphinx CSS */
+div.cell_output table {
+  border: none;
+  border-collapse: collapse;
+  border-spacing: 0;
+  color: black;
+  font-size: 1em;
+  table-layout: fixed;
+}
+
+div.cell_output thead {
+  border-bottom: 1px solid black;
+  vertical-align: bottom;
+}
+
+div.cell_output tr,
+div.cell_output th,
+div.cell_output td {
+  text-align: right;
+  vertical-align: middle;
+  padding: 0.5em 0.5em;
+  line-height: normal;
+  white-space: normal;
+  max-width: none;
+  border: none;
+}
+
+div.cell_output th {
+  font-weight: bold;
+}
+
+div.cell_output tbody tr:nth-child(odd) {
+  background: #f5f5f5;
+}
+
+div.cell_output tbody tr:hover {
+  background: rgba(66, 165, 245, 0.2);
+}
+
+/** source code line numbers **/
+span.linenos {
+  opacity: 0.5;
+}
+
+/* Inline text from `paste` operation */
+
+span.pasted-text {
+  font-weight: bold;
+}
+
+span.pasted-inline img {
+  max-height: 2em;
+}
+
+tbody span.pasted-inline img {
+  max-height: none;
+}
+
+/* Font colors for translated ANSI escape sequences
+Color values are copied from Jupyter Notebook
+https://github.com/jupyter/notebook/blob/52581f8eda9b319eb0390ac77fe5903c38f81e3e/notebook/static/notebook/less/ansicolors.less#L14-L21
+Background colors from
+https://nbsphinx.readthedocs.io/en/latest/code-cells.html#ANSI-Colors
+*/
+div.highlight .-Color-Bold {
+  font-weight: bold;
+}
+
+div.highlight .-Color[class*=-Black] {
+  color: #3E424D
+}
+
+div.highlight .-Color[class*=-Red] {
+  color: #E75C58
+}
+
+div.highlight .-Color[class*=-Green] {
+  color: #00A250
+}
+
+div.highlight .-Color[class*=-Yellow] {
+  color: #DDB62B
+}
+
+div.highlight .-Color[class*=-Blue] {
+  color: #208FFB
+}
+
+div.highlight .-Color[class*=-Magenta] {
+  color: #D160C4
+}
+
+div.highlight .-Color[class*=-Cyan] {
+  color: #60C6C8
+}
+
+div.highlight .-Color[class*=-White] {
+  color: #C5C1B4
+}
+
+div.highlight .-Color[class*=-BGBlack] {
+  background-color: #3E424D
+}
+
+div.highlight .-Color[class*=-BGRed] {
+  background-color: #E75C58
+}
+
+div.highlight .-Color[class*=-BGGreen] {
+  background-color: #00A250
+}
+
+div.highlight .-Color[class*=-BGYellow] {
+  background-color: #DDB62B
+}
+
+div.highlight .-Color[class*=-BGBlue] {
+  background-color: #208FFB
+}
+
+div.highlight .-Color[class*=-BGMagenta] {
+  background-color: #D160C4
+}
+
+div.highlight .-Color[class*=-BGCyan] {
+  background-color: #60C6C8
+}
+
+div.highlight .-Color[class*=-BGWhite] {
+  background-color: #C5C1B4
+}
+
+/* Font colors for 8-bit ANSI */
+
+div.highlight .-Color[class*=-C0] {
+  color: #000000
+}
+
+div.highlight .-Color[class*=-BGC0] {
+  background-color: #000000
+}
+
+div.highlight .-Color[class*=-C1] {
+  color: #800000
+}
+
+div.highlight .-Color[class*=-BGC1] {
+  background-color: #800000
+}
+
+div.highlight .-Color[class*=-C2] {
+  color: #008000
+}
+
+div.highlight .-Color[class*=-BGC2] {
+  background-color: #008000
+}
+
+div.highlight .-Color[class*=-C3] {
+  color: #808000
+}
+
+div.highlight .-Color[class*=-BGC3] {
+  background-color: #808000
+}
+
+div.highlight .-Color[class*=-C4] {
+  color: #000080
+}
+
+div.highlight .-Color[class*=-BGC4] {
+  background-color: #000080
+}
+
+div.highlight .-Color[class*=-C5] {
+  color: #800080
+}
+
+div.highlight .-Color[class*=-BGC5] {
+  background-color: #800080
+}
+
+div.highlight .-Color[class*=-C6] {
+  color: #008080
+}
+
+div.highlight .-Color[class*=-BGC6] {
+  background-color: #008080
+}
+
+div.highlight .-Color[class*=-C7] {
+  color: #C0C0C0
+}
+
+div.highlight .-Color[class*=-BGC7] {
+  background-color: #C0C0C0
+}
+
+div.highlight .-Color[class*=-C8] {
+  color: #808080
+}
+
+div.highlight .-Color[class*=-BGC8] {
+  background-color: #808080
+}
+
+div.highlight .-Color[class*=-C9] {
+  color: #FF0000
+}
+
+div.highlight .-Color[class*=-BGC9] {
+  background-color: #FF0000
+}
+
+div.highlight .-Color[class*=-C10] {
+  color: #00FF00
+}
+
+div.highlight .-Color[class*=-BGC10] {
+  background-color: #00FF00
+}
+
+div.highlight .-Color[class*=-C11] {
+  color: #FFFF00
+}
+
+div.highlight .-Color[class*=-BGC11] {
+  background-color: #FFFF00
+}
+
+div.highlight .-Color[class*=-C12] {
+  color: #0000FF
+}
+
+div.highlight .-Color[class*=-BGC12] {
+  background-color: #0000FF
+}
+
+div.highlight .-Color[class*=-C13] {
+  color: #FF00FF
+}
+
+div.highlight .-Color[class*=-BGC13] {
+  background-color: #FF00FF
+}
+
+div.highlight .-Color[class*=-C14] {
+  color: #00FFFF
+}
+
+div.highlight .-Color[class*=-BGC14] {
+  background-color: #00FFFF
+}
+
+div.highlight .-Color[class*=-C15] {
+  color: #FFFFFF
+}
+
+div.highlight .-Color[class*=-BGC15] {
+  background-color: #FFFFFF
+}
+
+div.highlight .-Color[class*=-C16] {
+  color: #000000
+}
+
+div.highlight .-Color[class*=-BGC16] {
+  background-color: #000000
+}
+
+div.highlight .-Color[class*=-C17] {
+  color: #00005F
+}
+
+div.highlight .-Color[class*=-BGC17] {
+  background-color: #00005F
+}
+
+div.highlight .-Color[class*=-C18] {
+  color: #000087
+}
+
+div.highlight .-Color[class*=-BGC18] {
+  background-color: #000087
+}
+
+div.highlight .-Color[class*=-C19] {
+  color: #0000AF
+}
+
+div.highlight .-Color[class*=-BGC19] {
+  background-color: #0000AF
+}
+
+div.highlight .-Color[class*=-C20] {
+  color: #0000D7
+}
+
+div.highlight .-Color[class*=-BGC20] {
+  background-color: #0000D7
+}
+
+div.highlight .-Color[class*=-C21] {
+  color: #0000FF
+}
+
+div.highlight .-Color[class*=-BGC21] {
+  background-color: #0000FF
+}
+
+div.highlight .-Color[class*=-C22] {
+  color: #005F00
+}
+
+div.highlight .-Color[class*=-BGC22] {
+  background-color: #005F00
+}
+
+div.highlight .-Color[class*=-C23] {
+  color: #005F5F
+}
+
+div.highlight .-Color[class*=-BGC23] {
+  background-color: #005F5F
+}
+
+div.highlight .-Color[class*=-C24] {
+  color: #005F87
+}
+
+div.highlight .-Color[class*=-BGC24] {
+  background-color: #005F87
+}
+
+div.highlight .-Color[class*=-C25] {
+  color: #005FAF
+}
+
+div.highlight .-Color[class*=-BGC25] {
+  background-color: #005FAF
+}
+
+div.highlight .-Color[class*=-C26] {
+  color: #005FD7
+}
+
+div.highlight .-Color[class*=-BGC26] {
+  background-color: #005FD7
+}
+
+div.highlight .-Color[class*=-C27] {
+  color: #005FFF
+}
+
+div.highlight .-Color[class*=-BGC27] {
+  background-color: #005FFF
+}
+
+div.highlight .-Color[class*=-C28] {
+  color: #008700
+}
+
+div.highlight .-Color[class*=-BGC28] {
+  background-color: #008700
+}
+
+div.highlight .-Color[class*=-C29] {
+  color: #00875F
+}
+
+div.highlight .-Color[class*=-BGC29] {
+  background-color: #00875F
+}
+
+div.highlight .-Color[class*=-C30] {
+  color: #008787
+}
+
+div.highlight .-Color[class*=-BGC30] {
+  background-color: #008787
+}
+
+div.highlight .-Color[class*=-C31] {
+  color: #0087AF
+}
+
+div.highlight .-Color[class*=-BGC31] {
+  background-color: #0087AF
+}
+
+div.highlight .-Color[class*=-C32] {
+  color: #0087D7
+}
+
+div.highlight .-Color[class*=-BGC32] {
+  background-color: #0087D7
+}
+
+div.highlight .-Color[class*=-C33] {
+  color: #0087FF
+}
+
+div.highlight .-Color[class*=-BGC33] {
+  background-color: #0087FF
+}
+
+div.highlight .-Color[class*=-C34] {
+  color: #00AF00
+}
+
+div.highlight .-Color[class*=-BGC34] {
+  background-color: #00AF00
+}
+
+div.highlight .-Color[class*=-C35] {
+  color: #00AF5F
+}
+
+div.highlight .-Color[class*=-BGC35] {
+  background-color: #00AF5F
+}
+
+div.highlight .-Color[class*=-C36] {
+  color: #00AF87
+}
+
+div.highlight .-Color[class*=-BGC36] {
+  background-color: #00AF87
+}
+
+div.highlight .-Color[class*=-C37] {
+  color: #00AFAF
+}
+
+div.highlight .-Color[class*=-BGC37] {
+  background-color: #00AFAF
+}
+
+div.highlight .-Color[class*=-C38] {
+  color: #00AFD7
+}
+
+div.highlight .-Color[class*=-BGC38] {
+  background-color: #00AFD7
+}
+
+div.highlight .-Color[class*=-C39] {
+  color: #00AFFF
+}
+
+div.highlight .-Color[class*=-BGC39] {
+  background-color: #00AFFF
+}
+
+div.highlight .-Color[class*=-C40] {
+  color: #00D700
+}
+
+div.highlight .-Color[class*=-BGC40] {
+  background-color: #00D700
+}
+
+div.highlight .-Color[class*=-C41] {
+  color: #00D75F
+}
+
+div.highlight .-Color[class*=-BGC41] {
+  background-color: #00D75F
+}
+
+div.highlight .-Color[class*=-C42] {
+  color: #00D787
+}
+
+div.highlight .-Color[class*=-BGC42] {
+  background-color: #00D787
+}
+
+div.highlight .-Color[class*=-C43] {
+  color: #00D7AF
+}
+
+div.highlight .-Color[class*=-BGC43] {
+  background-color: #00D7AF
+}
+
+div.highlight .-Color[class*=-C44] {
+  color: #00D7D7
+}
+
+div.highlight .-Color[class*=-BGC44] {
+  background-color: #00D7D7
+}
+
+div.highlight .-Color[class*=-C45] {
+  color: #00D7FF
+}
+
+div.highlight .-Color[class*=-BGC45] {
+  background-color: #00D7FF
+}
+
+div.highlight .-Color[class*=-C46] {
+  color: #00FF00
+}
+
+div.highlight .-Color[class*=-BGC46] {
+  background-color: #00FF00
+}
+
+div.highlight .-Color[class*=-C47] {
+  color: #00FF5F
+}
+
+div.highlight .-Color[class*=-BGC47] {
+  background-color: #00FF5F
+}
+
+div.highlight .-Color[class*=-C48] {
+  color: #00FF87
+}
+
+div.highlight .-Color[class*=-BGC48] {
+  background-color: #00FF87
+}
+
+div.highlight .-Color[class*=-C49] {
+  color: #00FFAF
+}
+
+div.highlight .-Color[class*=-BGC49] {
+  background-color: #00FFAF
+}
+
+div.highlight .-Color[class*=-C50] {
+  color: #00FFD7
+}
+
+div.highlight .-Color[class*=-BGC50] {
+  background-color: #00FFD7
+}
+
+div.highlight .-Color[class*=-C51] {
+  color: #00FFFF
+}
+
+div.highlight .-Color[class*=-BGC51] {
+  background-color: #00FFFF
+}
+
+div.highlight .-Color[class*=-C52] {
+  color: #5F0000
+}
+
+div.highlight .-Color[class*=-BGC52] {
+  background-color: #5F0000
+}
+
+div.highlight .-Color[class*=-C53] {
+  color: #5F005F
+}
+
+div.highlight .-Color[class*=-BGC53] {
+  background-color: #5F005F
+}
+
+div.highlight .-Color[class*=-C54] {
+  color: #5F0087
+}
+
+div.highlight .-Color[class*=-BGC54] {
+  background-color: #5F0087
+}
+
+div.highlight .-Color[class*=-C55] {
+  color: #5F00AF
+}
+
+div.highlight .-Color[class*=-BGC55] {
+  background-color: #5F00AF
+}
+
+div.highlight .-Color[class*=-C56] {
+  color: #5F00D7
+}
+
+div.highlight .-Color[class*=-BGC56] {
+  background-color: #5F00D7
+}
+
+div.highlight .-Color[class*=-C57] {
+  color: #5F00FF
+}
+
+div.highlight .-Color[class*=-BGC57] {
+  background-color: #5F00FF
+}
+
+div.highlight .-Color[class*=-C58] {
+  color: #5F5F00
+}
+
+div.highlight .-Color[class*=-BGC58] {
+  background-color: #5F5F00
+}
+
+div.highlight .-Color[class*=-C59] {
+  color: #5F5F5F
+}
+
+div.highlight .-Color[class*=-BGC59] {
+  background-color: #5F5F5F
+}
+
+div.highlight .-Color[class*=-C60] {
+  color: #5F5F87
+}
+
+div.highlight .-Color[class*=-BGC60] {
+  background-color: #5F5F87
+}
+
+div.highlight .-Color[class*=-C61] {
+  color: #5F5FAF
+}
+
+div.highlight .-Color[class*=-BGC61] {
+  background-color: #5F5FAF
+}
+
+div.highlight .-Color[class*=-C62] {
+  color: #5F5FD7
+}
+
+div.highlight .-Color[class*=-BGC62] {
+  background-color: #5F5FD7
+}
+
+div.highlight .-Color[class*=-C63] {
+  color: #5F5FFF
+}
+
+div.highlight .-Color[class*=-BGC63] {
+  background-color: #5F5FFF
+}
+
+div.highlight .-Color[class*=-C64] {
+  color: #5F8700
+}
+
+div.highlight .-Color[class*=-BGC64] {
+  background-color: #5F8700
+}
+
+div.highlight .-Color[class*=-C65] {
+  color: #5F875F
+}
+
+div.highlight .-Color[class*=-BGC65] {
+  background-color: #5F875F
+}
+
+div.highlight .-Color[class*=-C66] {
+  color: #5F8787
+}
+
+div.highlight .-Color[class*=-BGC66] {
+  background-color: #5F8787
+}
+
+div.highlight .-Color[class*=-C67] {
+  color: #5F87AF
+}
+
+div.highlight .-Color[class*=-BGC67] {
+  background-color: #5F87AF
+}
+
+div.highlight .-Color[class*=-C68] {
+  color: #5F87D7
+}
+
+div.highlight .-Color[class*=-BGC68] {
+  background-color: #5F87D7
+}
+
+div.highlight .-Color[class*=-C69] {
+  color: #5F87FF
+}
+
+div.highlight .-Color[class*=-BGC69] {
+  background-color: #5F87FF
+}
+
+div.highlight .-Color[class*=-C70] {
+  color: #5FAF00
+}
+
+div.highlight .-Color[class*=-BGC70] {
+  background-color: #5FAF00
+}
+
+div.highlight .-Color[class*=-C71] {
+  color: #5FAF5F
+}
+
+div.highlight .-Color[class*=-BGC71] {
+  background-color: #5FAF5F
+}
+
+div.highlight .-Color[class*=-C72] {
+  color: #5FAF87
+}
+
+div.highlight .-Color[class*=-BGC72] {
+  background-color: #5FAF87
+}
+
+div.highlight .-Color[class*=-C73] {
+  color: #5FAFAF
+}
+
+div.highlight .-Color[class*=-BGC73] {
+  background-color: #5FAFAF
+}
+
+div.highlight .-Color[class*=-C74] {
+  color: #5FAFD7
+}
+
+div.highlight .-Color[class*=-BGC74] {
+  background-color: #5FAFD7
+}
+
+div.highlight .-Color[class*=-C75] {
+  color: #5FAFFF
+}
+
+div.highlight .-Color[class*=-BGC75] {
+  background-color: #5FAFFF
+}
+
+div.highlight .-Color[class*=-C76] {
+  color: #5FD700
+}
+
+div.highlight .-Color[class*=-BGC76] {
+  background-color: #5FD700
+}
+
+div.highlight .-Color[class*=-C77] {
+  color: #5FD75F
+}
+
+div.highlight .-Color[class*=-BGC77] {
+  background-color: #5FD75F
+}
+
+div.highlight .-Color[class*=-C78] {
+  color: #5FD787
+}
+
+div.highlight .-Color[class*=-BGC78] {
+  background-color: #5FD787
+}
+
+div.highlight .-Color[class*=-C79] {
+  color: #5FD7AF
+}
+
+div.highlight .-Color[class*=-BGC79] {
+  background-color: #5FD7AF
+}
+
+div.highlight .-Color[class*=-C80] {
+  color: #5FD7D7
+}
+
+div.highlight .-Color[class*=-BGC80] {
+  background-color: #5FD7D7
+}
+
+div.highlight .-Color[class*=-C81] {
+  color: #5FD7FF
+}
+
+div.highlight .-Color[class*=-BGC81] {
+  background-color: #5FD7FF
+}
+
+div.highlight .-Color[class*=-C82] {
+  color: #5FFF00
+}
+
+div.highlight .-Color[class*=-BGC82] {
+  background-color: #5FFF00
+}
+
+div.highlight .-Color[class*=-C83] {
+  color: #5FFF5F
+}
+
+div.highlight .-Color[class*=-BGC83] {
+  background-color: #5FFF5F
+}
+
+div.highlight .-Color[class*=-C84] {
+  color: #5FFF87
+}
+
+div.highlight .-Color[class*=-BGC84] {
+  background-color: #5FFF87
+}
+
+div.highlight .-Color[class*=-C85] {
+  color: #5FFFAF
+}
+
+div.highlight .-Color[class*=-BGC85] {
+  background-color: #5FFFAF
+}
+
+div.highlight .-Color[class*=-C86] {
+  color: #5FFFD7
+}
+
+div.highlight .-Color[class*=-BGC86] {
+  background-color: #5FFFD7
+}
+
+div.highlight .-Color[class*=-C87] {
+  color: #5FFFFF
+}
+
+div.highlight .-Color[class*=-BGC87] {
+  background-color: #5FFFFF
+}
+
+div.highlight .-Color[class*=-C88] {
+  color: #870000
+}
+
+div.highlight .-Color[class*=-BGC88] {
+  background-color: #870000
+}
+
+div.highlight .-Color[class*=-C89] {
+  color: #87005F
+}
+
+div.highlight .-Color[class*=-BGC89] {
+  background-color: #87005F
+}
+
+div.highlight .-Color[class*=-C90] {
+  color: #870087
+}
+
+div.highlight .-Color[class*=-BGC90] {
+  background-color: #870087
+}
+
+div.highlight .-Color[class*=-C91] {
+  color: #8700AF
+}
+
+div.highlight .-Color[class*=-BGC91] {
+  background-color: #8700AF
+}
+
+div.highlight .-Color[class*=-C92] {
+  color: #8700D7
+}
+
+div.highlight .-Color[class*=-BGC92] {
+  background-color: #8700D7
+}
+
+div.highlight .-Color[class*=-C93] {
+  color: #8700FF
+}
+
+div.highlight .-Color[class*=-BGC93] {
+  background-color: #8700FF
+}
+
+div.highlight .-Color[class*=-C94] {
+  color: #875F00
+}
+
+div.highlight .-Color[class*=-BGC94] {
+  background-color: #875F00
+}
+
+div.highlight .-Color[class*=-C95] {
+  color: #875F5F
+}
+
+div.highlight .-Color[class*=-BGC95] {
+  background-color: #875F5F
+}
+
+div.highlight .-Color[class*=-C96] {
+  color: #875F87
+}
+
+div.highlight .-Color[class*=-BGC96] {
+  background-color: #875F87
+}
+
+div.highlight .-Color[class*=-C97] {
+  color: #875FAF
+}
+
+div.highlight .-Color[class*=-BGC97] {
+  background-color: #875FAF
+}
+
+div.highlight .-Color[class*=-C98] {
+  color: #875FD7
+}
+
+div.highlight .-Color[class*=-BGC98] {
+  background-color: #875FD7
+}
+
+div.highlight .-Color[class*=-C99] {
+  color: #875FFF
+}
+
+div.highlight .-Color[class*=-BGC99] {
+  background-color: #875FFF
+}
+
+div.highlight .-Color[class*=-C100] {
+  color: #878700
+}
+
+div.highlight .-Color[class*=-BGC100] {
+  background-color: #878700
+}
+
+div.highlight .-Color[class*=-C101] {
+  color: #87875F
+}
+
+div.highlight .-Color[class*=-BGC101] {
+  background-color: #87875F
+}
+
+div.highlight .-Color[class*=-C102] {
+  color: #878787
+}
+
+div.highlight .-Color[class*=-BGC102] {
+  background-color: #878787
+}
+
+div.highlight .-Color[class*=-C103] {
+  color: #8787AF
+}
+
+div.highlight .-Color[class*=-BGC103] {
+  background-color: #8787AF
+}
+
+div.highlight .-Color[class*=-C104] {
+  color: #8787D7
+}
+
+div.highlight .-Color[class*=-BGC104] {
+  background-color: #8787D7
+}
+
+div.highlight .-Color[class*=-C105] {
+  color: #8787FF
+}
+
+div.highlight .-Color[class*=-BGC105] {
+  background-color: #8787FF
+}
+
+div.highlight .-Color[class*=-C106] {
+  color: #87AF00
+}
+
+div.highlight .-Color[class*=-BGC106] {
+  background-color: #87AF00
+}
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+}
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+}
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+}
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+}
+
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+}
+
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+}
+
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+}
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+}
+
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+}
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+}
+
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+}
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+}
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+}
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+}
+
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+}
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+}
+
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+}
+
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+}
+
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+}
+
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+}
+
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+}
+
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+}
+
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+}
+
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+}
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+}
+
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+}
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+}
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+}
+
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+}
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+}
+
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+}
+
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+}
+
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+}
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+}
+
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+}
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+}
+
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+}
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+}
+
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
+
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+}
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+}
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+}
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+}
+
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+  color: #AFAF5F
+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
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+}
+
+div.highlight .-Color[class*=-BGC222] {
+  background-color: #FFD787
+}
+
+div.highlight .-Color[class*=-C223] {
+  color: #FFD7AF
+}
+
+div.highlight .-Color[class*=-BGC223] {
+  background-color: #FFD7AF
+}
+
+div.highlight .-Color[class*=-C224] {
+  color: #FFD7D7
+}
+
+div.highlight .-Color[class*=-BGC224] {
+  background-color: #FFD7D7
+}
+
+div.highlight .-Color[class*=-C225] {
+  color: #FFD7FF
+}
+
+div.highlight .-Color[class*=-BGC225] {
+  background-color: #FFD7FF
+}
+
+div.highlight .-Color[class*=-C226] {
+  color: #FFFF00
+}
+
+div.highlight .-Color[class*=-BGC226] {
+  background-color: #FFFF00
+}
+
+div.highlight .-Color[class*=-C227] {
+  color: #FFFF5F
+}
+
+div.highlight .-Color[class*=-BGC227] {
+  background-color: #FFFF5F
+}
+
+div.highlight .-Color[class*=-C228] {
+  color: #FFFF87
+}
+
+div.highlight .-Color[class*=-BGC228] {
+  background-color: #FFFF87
+}
+
+div.highlight .-Color[class*=-C229] {
+  color: #FFFFAF
+}
+
+div.highlight .-Color[class*=-BGC229] {
+  background-color: #FFFFAF
+}
+
+div.highlight .-Color[class*=-C230] {
+  color: #FFFFD7
+}
+
+div.highlight .-Color[class*=-BGC230] {
+  background-color: #FFFFD7
+}
+
+div.highlight .-Color[class*=-C231] {
+  color: #FFFFFF
+}
+
+div.highlight .-Color[class*=-BGC231] {
+  background-color: #FFFFFF
+}
+
+div.highlight .-Color[class*=-C232] {
+  color: #080808
+}
+
+div.highlight .-Color[class*=-BGC232] {
+  background-color: #080808
+}
+
+div.highlight .-Color[class*=-C233] {
+  color: #121212
+}
+
+div.highlight .-Color[class*=-BGC233] {
+  background-color: #121212
+}
+
+div.highlight .-Color[class*=-C234] {
+  color: #1C1C1C
+}
+
+div.highlight .-Color[class*=-BGC234] {
+  background-color: #1C1C1C
+}
+
+div.highlight .-Color[class*=-C235] {
+  color: #262626
+}
+
+div.highlight .-Color[class*=-BGC235] {
+  background-color: #262626
+}
+
+div.highlight .-Color[class*=-C236] {
+  color: #303030
+}
+
+div.highlight .-Color[class*=-BGC236] {
+  background-color: #303030
+}
+
+div.highlight .-Color[class*=-C237] {
+  color: #3A3A3A
+}
+
+div.highlight .-Color[class*=-BGC237] {
+  background-color: #3A3A3A
+}
+
+div.highlight .-Color[class*=-C238] {
+  color: #444444
+}
+
+div.highlight .-Color[class*=-BGC238] {
+  background-color: #444444
+}
+
+div.highlight .-Color[class*=-C239] {
+  color: #4E4E4E
+}
+
+div.highlight .-Color[class*=-BGC239] {
+  background-color: #4E4E4E
+}
+
+div.highlight .-Color[class*=-C240] {
+  color: #585858
+}
+
+div.highlight .-Color[class*=-BGC240] {
+  background-color: #585858
+}
+
+div.highlight .-Color[class*=-C241] {
+  color: #626262
+}
+
+div.highlight .-Color[class*=-BGC241] {
+  background-color: #626262
+}
+
+div.highlight .-Color[class*=-C242] {
+  color: #6C6C6C
+}
+
+div.highlight .-Color[class*=-BGC242] {
+  background-color: #6C6C6C
+}
+
+div.highlight .-Color[class*=-C243] {
+  color: #767676
+}
+
+div.highlight .-Color[class*=-BGC243] {
+  background-color: #767676
+}
+
+div.highlight .-Color[class*=-C244] {
+  color: #808080
+}
+
+div.highlight .-Color[class*=-BGC244] {
+  background-color: #808080
+}
+
+div.highlight .-Color[class*=-C245] {
+  color: #8A8A8A
+}
+
+div.highlight .-Color[class*=-BGC245] {
+  background-color: #8A8A8A
+}
+
+div.highlight .-Color[class*=-C246] {
+  color: #949494
+}
+
+div.highlight .-Color[class*=-BGC246] {
+  background-color: #949494
+}
+
+div.highlight .-Color[class*=-C247] {
+  color: #9E9E9E
+}
+
+div.highlight .-Color[class*=-BGC247] {
+  background-color: #9E9E9E
+}
+
+div.highlight .-Color[class*=-C248] {
+  color: #A8A8A8
+}
+
+div.highlight .-Color[class*=-BGC248] {
+  background-color: #A8A8A8
+}
+
+div.highlight .-Color[class*=-C249] {
+  color: #B2B2B2
+}
+
+div.highlight .-Color[class*=-BGC249] {
+  background-color: #B2B2B2
+}
+
+div.highlight .-Color[class*=-C250] {
+  color: #BCBCBC
+}
+
+div.highlight .-Color[class*=-BGC250] {
+  background-color: #BCBCBC
+}
+
+div.highlight .-Color[class*=-C251] {
+  color: #C6C6C6
+}
+
+div.highlight .-Color[class*=-BGC251] {
+  background-color: #C6C6C6
+}
+
+div.highlight .-Color[class*=-C252] {
+  color: #D0D0D0
+}
+
+div.highlight .-Color[class*=-BGC252] {
+  background-color: #D0D0D0
+}
+
+div.highlight .-Color[class*=-C253] {
+  color: #DADADA
+}
+
+div.highlight .-Color[class*=-BGC253] {
+  background-color: #DADADA
+}
+
+div.highlight .-Color[class*=-C254] {
+  color: #E4E4E4
+}
+
+div.highlight .-Color[class*=-BGC254] {
+  background-color: #E4E4E4
+}
+
+div.highlight .-Color[class*=-C255] {
+  color: #EEEEEE
+}
+
+div.highlight .-Color[class*=-BGC255] {
+  background-color: #EEEEEE
+}
diff --git a/_static/plus.png b/_static/plus.png
new file mode 100644
index 00000000..7107cec9
Binary files /dev/null and b/_static/plus.png differ
diff --git a/_static/pygments.css b/_static/pygments.css
new file mode 100644
index 00000000..c15243c2
--- /dev/null
+++ b/_static/pygments.css
@@ -0,0 +1,85 @@
+pre { line-height: 125%; }
+td.linenos .normal { color: #3c4354; background-color: transparent; padding-left: 5px; padding-right: 5px; }
+span.linenos { color: #3c4354; background-color: transparent; padding-left: 5px; padding-right: 5px; }
+td.linenos .special { color: #3c4354; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; }
+span.linenos.special { color: #3c4354; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; }
+.highlight .hll { background-color: #6e7681 }
+.highlight { background: #1d2331; color: #d4d2c8 }
+.highlight .c { color: #7e8aa1 } /* Comment */
+.highlight .err { color: #f88f7f } /* Error */
+.highlight .esc { color: #d4d2c8 } /* Escape */
+.highlight .g { color: #d4d2c8 } /* Generic */
+.highlight .k { color: #FFAD66 } /* Keyword */
+.highlight .l { color: #D5FF80 } /* Literal */
+.highlight .n { color: #d4d2c8 } /* Name */
+.highlight .o { color: #FFAD66 } /* Operator */
+.highlight .x { color: #d4d2c8 } /* Other */
+.highlight .p { color: #d4d2c8 } /* Punctuation */
+.highlight .ch { color: #f88f7f; font-style: italic } /* Comment.Hashbang */
+.highlight .cm { color: #7e8aa1 } /* Comment.Multiline */
+.highlight .cp { color: #FFAD66; font-weight: bold } /* Comment.Preproc */
+.highlight .cpf { color: #7e8aa1 } /* Comment.PreprocFile */
+.highlight .c1 { color: #7e8aa1 } /* Comment.Single */
+.highlight .cs { color: #7e8aa1; font-style: italic } /* Comment.Special */
+.highlight .gd { color: #f88f7f; background-color: #3d1e20 } /* Generic.Deleted */
+.highlight .ge { color: #d4d2c8; font-style: italic } /* Generic.Emph */
+.highlight .ges { color: #d4d2c8 } /* Generic.EmphStrong */
+.highlight .gr { color: #f88f7f } /* Generic.Error */
+.highlight .gh { color: #d4d2c8 } /* Generic.Heading */
+.highlight .gi { color: #6ad4af; background-color: #19362c } /* Generic.Inserted */
+.highlight .go { color: #7e8aa1 } /* Generic.Output */
+.highlight .gp { color: #d4d2c8 } /* Generic.Prompt */
+.highlight .gs { color: #d4d2c8; font-weight: bold } /* Generic.Strong */
+.highlight .gu { color: #d4d2c8 } /* Generic.Subheading */
+.highlight .gt { color: #f88f7f } /* Generic.Traceback */
+.highlight .kc { color: #FFAD66 } /* Keyword.Constant */
+.highlight .kd { color: #FFAD66 } /* Keyword.Declaration */
+.highlight .kn { color: #FFAD66 } /* Keyword.Namespace */
+.highlight .kp { color: #FFAD66 } /* Keyword.Pseudo */
+.highlight .kr { color: #FFAD66 } /* Keyword.Reserved */
+.highlight .kt { color: #73D0FF } /* Keyword.Type */
+.highlight .ld { color: #D5FF80 } /* Literal.Date */
+.highlight .m { color: #DFBFFF } /* Literal.Number */
+.highlight .s { color: #D5FF80 } /* Literal.String */
+.highlight .na { color: #FFD173 } /* Name.Attribute */
+.highlight .nb { color: #FFD173 } /* Name.Builtin */
+.highlight .nc { color: #73D0FF } /* Name.Class */
+.highlight .no { color: #FFD173 } /* Name.Constant */
+.highlight .nd { color: #7e8aa1; font-weight: bold; font-style: italic } /* Name.Decorator */
+.highlight .ni { color: #95E6CB } /* Name.Entity */
+.highlight .ne { color: #73D0FF } /* Name.Exception */
+.highlight .nf { color: #FFD173 } /* Name.Function */
+.highlight .nl { color: #d4d2c8 } /* Name.Label */
+.highlight .nn { color: #d4d2c8 } /* Name.Namespace */
+.highlight .nx { color: #d4d2c8 } /* Name.Other */
+.highlight .py { color: #FFD173 } /* Name.Property */
+.highlight .nt { color: #5CCFE6 } /* Name.Tag */
+.highlight .nv { color: #d4d2c8 } /* Name.Variable */
+.highlight .ow { color: #FFAD66 } /* Operator.Word */
+.highlight .pm { color: #d4d2c8 } /* Punctuation.Marker */
+.highlight .w { color: #d4d2c8 } /* Text.Whitespace */
+.highlight .mb { color: #DFBFFF } /* Literal.Number.Bin */
+.highlight .mf { color: #DFBFFF } /* Literal.Number.Float */
+.highlight .mh { color: #DFBFFF } /* Literal.Number.Hex */
+.highlight .mi { color: #DFBFFF } /* Literal.Number.Integer */
+.highlight .mo { color: #DFBFFF } /* Literal.Number.Oct */
+.highlight .sa { color: #F29E74 } /* Literal.String.Affix */
+.highlight .sb { color: #D5FF80 } /* Literal.String.Backtick */
+.highlight .sc { color: #D5FF80 } /* Literal.String.Char */
+.highlight .dl { color: #D5FF80 } /* Literal.String.Delimiter */
+.highlight .sd { color: #7e8aa1 } /* Literal.String.Doc */
+.highlight .s2 { color: #D5FF80 } /* Literal.String.Double */
+.highlight .se { color: #95E6CB } /* Literal.String.Escape */
+.highlight .sh { color: #D5FF80 } /* Literal.String.Heredoc */
+.highlight .si { color: #95E6CB } /* Literal.String.Interpol */
+.highlight .sx { color: #95E6CB } /* Literal.String.Other */
+.highlight .sr { color: #95E6CB } /* Literal.String.Regex */
+.highlight .s1 { color: #D5FF80 } /* Literal.String.Single */
+.highlight .ss { color: #DFBFFF } /* Literal.String.Symbol */
+.highlight .bp { color: #5CCFE6 } /* Name.Builtin.Pseudo */
+.highlight .fm { color: #FFD173 } /* Name.Function.Magic */
+.highlight .vc { color: #d4d2c8 } /* Name.Variable.Class */
+.highlight .vg { color: #d4d2c8 } /* Name.Variable.Global */
+.highlight .vi { color: #d4d2c8 } /* Name.Variable.Instance */
+.highlight .vm { color: #d4d2c8 } /* Name.Variable.Magic */
+.highlight .il { color: #DFBFFF } /* Literal.Number.Integer.Long */
\ No newline at end of file
diff --git a/_static/searchtools.js b/_static/searchtools.js
new file mode 100644
index 00000000..7918c3fa
--- /dev/null
+++ b/_static/searchtools.js
@@ -0,0 +1,574 @@
+/*
+ * searchtools.js
+ * ~~~~~~~~~~~~~~~~
+ *
+ * Sphinx JavaScript utilities for the full-text search.
+ *
+ * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+"use strict";
+
+/**
+ * Simple result scoring code.
+ */
+if (typeof Scorer === "undefined") {
+  var Scorer = {
+    // Implement the following function to further tweak the score for each result
+    // The function takes a result array [docname, title, anchor, descr, score, filename]
+    // and returns the new score.
+    /*
+    score: result => {
+      const [docname, title, anchor, descr, score, filename] = result
+      return score
+    },
+    */
+
+    // query matches the full name of an object
+    objNameMatch: 11,
+    // or matches in the last dotted part of the object name
+    objPartialMatch: 6,
+    // Additive scores depending on the priority of the object
+    objPrio: {
+      0: 15, // used to be importantResults
+      1: 5, // used to be objectResults
+      2: -5, // used to be unimportantResults
+    },
+    //  Used when the priority is not in the mapping.
+    objPrioDefault: 0,
+
+    // query found in title
+    title: 15,
+    partialTitle: 7,
+    // query found in terms
+    term: 5,
+    partialTerm: 2,
+  };
+}
+
+const _removeChildren = (element) => {
+  while (element && element.lastChild) element.removeChild(element.lastChild);
+};
+
+/**
+ * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping
+ */
+const _escapeRegExp = (string) =>
+  string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string
+
+const _displayItem = (item, searchTerms, highlightTerms) => {
+  const docBuilder = DOCUMENTATION_OPTIONS.BUILDER;
+  const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX;
+  const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX;
+  const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY;
+  const contentRoot = document.documentElement.dataset.content_root;
+
+  const [docName, title, anchor, descr, score, _filename] = item;
+
+  let listItem = document.createElement("li");
+  let requestUrl;
+  let linkUrl;
+  if (docBuilder === "dirhtml") {
+    // dirhtml builder
+    let dirname = docName + "/";
+    if (dirname.match(/\/index\/$/))
+      dirname = dirname.substring(0, dirname.length - 6);
+    else if (dirname === "index/") dirname = "";
+    requestUrl = contentRoot + dirname;
+    linkUrl = requestUrl;
+  } else {
+    // normal html builders
+    requestUrl = contentRoot + docName + docFileSuffix;
+    linkUrl = docName + docLinkSuffix;
+  }
+  let linkEl = listItem.appendChild(document.createElement("a"));
+  linkEl.href = linkUrl + anchor;
+  linkEl.dataset.score = score;
+  linkEl.innerHTML = title;
+  if (descr) {
+    listItem.appendChild(document.createElement("span")).innerHTML =
+      " (" + descr + ")";
+    // highlight search terms in the description
+    if (SPHINX_HIGHLIGHT_ENABLED)  // set in sphinx_highlight.js
+      highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted"));
+  }
+  else if (showSearchSummary)
+    fetch(requestUrl)
+      .then((responseData) => responseData.text())
+      .then((data) => {
+        if (data)
+          listItem.appendChild(
+            Search.makeSearchSummary(data, searchTerms)
+          );
+        // highlight search terms in the summary
+        if (SPHINX_HIGHLIGHT_ENABLED)  // set in sphinx_highlight.js
+          highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted"));
+      });
+  Search.output.appendChild(listItem);
+};
+const _finishSearch = (resultCount) => {
+  Search.stopPulse();
+  Search.title.innerText = _("Search Results");
+  if (!resultCount)
+    Search.status.innerText = Documentation.gettext(
+      "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories."
+    );
+  else
+    Search.status.innerText = _(
+      `Search finished, found ${resultCount} page(s) matching the search query.`
+    );
+};
+const _displayNextItem = (
+  results,
+  resultCount,
+  searchTerms,
+  highlightTerms,
+) => {
+  // results left, load the summary and display it
+  // this is intended to be dynamic (don't sub resultsCount)
+  if (results.length) {
+    _displayItem(results.pop(), searchTerms, highlightTerms);
+    setTimeout(
+      () => _displayNextItem(results, resultCount, searchTerms, highlightTerms),
+      5
+    );
+  }
+  // search finished, update title and status message
+  else _finishSearch(resultCount);
+};
+
+/**
+ * Default splitQuery function. Can be overridden in ``sphinx.search`` with a
+ * custom function per language.
+ *
+ * The regular expression works by splitting the string on consecutive characters
+ * that are not Unicode letters, numbers, underscores, or emoji characters.
+ * This is the same as ``\W+`` in Python, preserving the surrogate pair area.
+ */
+if (typeof splitQuery === "undefined") {
+  var splitQuery = (query) => query
+      .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu)
+      .filter(term => term)  // remove remaining empty strings
+}
+
+/**
+ * Search Module
+ */
+const Search = {
+  _index: null,
+  _queued_query: null,
+  _pulse_status: -1,
+
+  htmlToText: (htmlString) => {
+    const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html');
+    htmlElement.querySelectorAll(".headerlink").forEach((el) => { el.remove() });
+    const docContent = htmlElement.querySelector('[role="main"]');
+    if (docContent !== undefined) return docContent.textContent;
+    console.warn(
+      "Content block not found. Sphinx search tries to obtain it via '[role=main]'. Could you check your theme or template."
+    );
+    return "";
+  },
+
+  init: () => {
+    const query = new URLSearchParams(window.location.search).get("q");
+    document
+      .querySelectorAll('input[name="q"]')
+      .forEach((el) => (el.value = query));
+    if (query) Search.performSearch(query);
+  },
+
+  loadIndex: (url) =>
+    (document.body.appendChild(document.createElement("script")).src = url),
+
+  setIndex: (index) => {
+    Search._index = index;
+    if (Search._queued_query !== null) {
+      const query = Search._queued_query;
+      Search._queued_query = null;
+      Search.query(query);
+    }
+  },
+
+  hasIndex: () => Search._index !== null,
+
+  deferQuery: (query) => (Search._queued_query = query),
+
+  stopPulse: () => (Search._pulse_status = -1),
+
+  startPulse: () => {
+    if (Search._pulse_status >= 0) return;
+
+    const pulse = () => {
+      Search._pulse_status = (Search._pulse_status + 1) % 4;
+      Search.dots.innerText = ".".repeat(Search._pulse_status);
+      if (Search._pulse_status >= 0) window.setTimeout(pulse, 500);
+    };
+    pulse();
+  },
+
+  /**
+   * perform a search for something (or wait until index is loaded)
+   */
+  performSearch: (query) => {
+    // create the required interface elements
+    const searchText = document.createElement("h2");
+    searchText.textContent = _("Searching");
+    const searchSummary = document.createElement("p");
+    searchSummary.classList.add("search-summary");
+    searchSummary.innerText = "";
+    const searchList = document.createElement("ul");
+    searchList.classList.add("search");
+
+    const out = document.getElementById("search-results");
+    Search.title = out.appendChild(searchText);
+    Search.dots = Search.title.appendChild(document.createElement("span"));
+    Search.status = out.appendChild(searchSummary);
+    Search.output = out.appendChild(searchList);
+
+    const searchProgress = document.getElementById("search-progress");
+    // Some themes don't use the search progress node
+    if (searchProgress) {
+      searchProgress.innerText = _("Preparing search...");
+    }
+    Search.startPulse();
+
+    // index already loaded, the browser was quick!
+    if (Search.hasIndex()) Search.query(query);
+    else Search.deferQuery(query);
+  },
+
+  /**
+   * execute search (requires search index to be loaded)
+   */
+  query: (query) => {
+    const filenames = Search._index.filenames;
+    const docNames = Search._index.docnames;
+    const titles = Search._index.titles;
+    const allTitles = Search._index.alltitles;
+    const indexEntries = Search._index.indexentries;
+
+    // stem the search terms and add them to the correct list
+    const stemmer = new Stemmer();
+    const searchTerms = new Set();
+    const excludedTerms = new Set();
+    const highlightTerms = new Set();
+    const objectTerms = new Set(splitQuery(query.toLowerCase().trim()));
+    splitQuery(query.trim()).forEach((queryTerm) => {
+      const queryTermLower = queryTerm.toLowerCase();
+
+      // maybe skip this "word"
+      // stopwords array is from language_data.js
+      if (
+        stopwords.indexOf(queryTermLower) !== -1 ||
+        queryTerm.match(/^\d+$/)
+      )
+        return;
+
+      // stem the word
+      let word = stemmer.stemWord(queryTermLower);
+      // select the correct list
+      if (word[0] === "-") excludedTerms.add(word.substr(1));
+      else {
+        searchTerms.add(word);
+        highlightTerms.add(queryTermLower);
+      }
+    });
+
+    if (SPHINX_HIGHLIGHT_ENABLED) {  // set in sphinx_highlight.js
+      localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" "))
+    }
+
+    // console.debug("SEARCH: searching for:");
+    // console.info("required: ", [...searchTerms]);
+    // console.info("excluded: ", [...excludedTerms]);
+
+    // array of [docname, title, anchor, descr, score, filename]
+    let results = [];
+    _removeChildren(document.getElementById("search-progress"));
+
+    const queryLower = query.toLowerCase();
+    for (const [title, foundTitles] of Object.entries(allTitles)) {
+      if (title.toLowerCase().includes(queryLower) && (queryLower.length >= title.length/2)) {
+        for (const [file, id] of foundTitles) {
+          let score = Math.round(100 * queryLower.length / title.length)
+          results.push([
+            docNames[file],
+            titles[file] !== title ? `${titles[file]} > ${title}` : title,
+            id !== null ? "#" + id : "",
+            null,
+            score,
+            filenames[file],
+          ]);
+        }
+      }
+    }
+
+    // search for explicit entries in index directives
+    for (const [entry, foundEntries] of Object.entries(indexEntries)) {
+      if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) {
+        for (const [file, id] of foundEntries) {
+          let score = Math.round(100 * queryLower.length / entry.length)
+          results.push([
+            docNames[file],
+            titles[file],
+            id ? "#" + id : "",
+            null,
+            score,
+            filenames[file],
+          ]);
+        }
+      }
+    }
+
+    // lookup as object
+    objectTerms.forEach((term) =>
+      results.push(...Search.performObjectSearch(term, objectTerms))
+    );
+
+    // lookup as search terms in fulltext
+    results.push(...Search.performTermsSearch(searchTerms, excludedTerms));
+
+    // let the scorer override scores with a custom scoring function
+    if (Scorer.score) results.forEach((item) => (item[4] = Scorer.score(item)));
+
+    // now sort the results by score (in opposite order of appearance, since the
+    // display function below uses pop() to retrieve items) and then
+    // alphabetically
+    results.sort((a, b) => {
+      const leftScore = a[4];
+      const rightScore = b[4];
+      if (leftScore === rightScore) {
+        // same score: sort alphabetically
+        const leftTitle = a[1].toLowerCase();
+        const rightTitle = b[1].toLowerCase();
+        if (leftTitle === rightTitle) return 0;
+        return leftTitle > rightTitle ? -1 : 1; // inverted is intentional
+      }
+      return leftScore > rightScore ? 1 : -1;
+    });
+
+    // remove duplicate search results
+    // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept
+    let seen = new Set();
+    results = results.reverse().reduce((acc, result) => {
+      let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(',');
+      if (!seen.has(resultStr)) {
+        acc.push(result);
+        seen.add(resultStr);
+      }
+      return acc;
+    }, []);
+
+    results = results.reverse();
+
+    // for debugging
+    //Search.lastresults = results.slice();  // a copy
+    // console.info("search results:", Search.lastresults);
+
+    // print the results
+    _displayNextItem(results, results.length, searchTerms, highlightTerms);
+  },
+
+  /**
+   * search for object names
+   */
+  performObjectSearch: (object, objectTerms) => {
+    const filenames = Search._index.filenames;
+    const docNames = Search._index.docnames;
+    const objects = Search._index.objects;
+    const objNames = Search._index.objnames;
+    const titles = Search._index.titles;
+
+    const results = [];
+
+    const objectSearchCallback = (prefix, match) => {
+      const name = match[4]
+      const fullname = (prefix ? prefix + "." : "") + name;
+      const fullnameLower = fullname.toLowerCase();
+      if (fullnameLower.indexOf(object) < 0) return;
+
+      let score = 0;
+      const parts = fullnameLower.split(".");
+
+      // check for different match types: exact matches of full name or
+      // "last name" (i.e. last dotted part)
+      if (fullnameLower === object || parts.slice(-1)[0] === object)
+        score += Scorer.objNameMatch;
+      else if (parts.slice(-1)[0].indexOf(object) > -1)
+        score += Scorer.objPartialMatch; // matches in last name
+
+      const objName = objNames[match[1]][2];
+      const title = titles[match[0]];
+
+      // If more than one term searched for, we require other words to be
+      // found in the name/title/description
+      const otherTerms = new Set(objectTerms);
+      otherTerms.delete(object);
+      if (otherTerms.size > 0) {
+        const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase();
+        if (
+          [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0)
+        )
+          return;
+      }
+
+      let anchor = match[3];
+      if (anchor === "") anchor = fullname;
+      else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname;
+
+      const descr = objName + _(", in ") + title;
+
+      // add custom score for some objects according to scorer
+      if (Scorer.objPrio.hasOwnProperty(match[2]))
+        score += Scorer.objPrio[match[2]];
+      else score += Scorer.objPrioDefault;
+
+      results.push([
+        docNames[match[0]],
+        fullname,
+        "#" + anchor,
+        descr,
+        score,
+        filenames[match[0]],
+      ]);
+    };
+    Object.keys(objects).forEach((prefix) =>
+      objects[prefix].forEach((array) =>
+        objectSearchCallback(prefix, array)
+      )
+    );
+    return results;
+  },
+
+  /**
+   * search for full-text terms in the index
+   */
+  performTermsSearch: (searchTerms, excludedTerms) => {
+    // prepare search
+    const terms = Search._index.terms;
+    const titleTerms = Search._index.titleterms;
+    const filenames = Search._index.filenames;
+    const docNames = Search._index.docnames;
+    const titles = Search._index.titles;
+
+    const scoreMap = new Map();
+    const fileMap = new Map();
+
+    // perform the search on the required terms
+    searchTerms.forEach((word) => {
+      const files = [];
+      const arr = [
+        { files: terms[word], score: Scorer.term },
+        { files: titleTerms[word], score: Scorer.title },
+      ];
+      // add support for partial matches
+      if (word.length > 2) {
+        const escapedWord = _escapeRegExp(word);
+        Object.keys(terms).forEach((term) => {
+          if (term.match(escapedWord) && !terms[word])
+            arr.push({ files: terms[term], score: Scorer.partialTerm });
+        });
+        Object.keys(titleTerms).forEach((term) => {
+          if (term.match(escapedWord) && !titleTerms[word])
+            arr.push({ files: titleTerms[word], score: Scorer.partialTitle });
+        });
+      }
+
+      // no match but word was a required one
+      if (arr.every((record) => record.files === undefined)) return;
+
+      // found search word in contents
+      arr.forEach((record) => {
+        if (record.files === undefined) return;
+
+        let recordFiles = record.files;
+        if (recordFiles.length === undefined) recordFiles = [recordFiles];
+        files.push(...recordFiles);
+
+        // set score for the word in each file
+        recordFiles.forEach((file) => {
+          if (!scoreMap.has(file)) scoreMap.set(file, {});
+          scoreMap.get(file)[word] = record.score;
+        });
+      });
+
+      // create the mapping
+      files.forEach((file) => {
+        if (fileMap.has(file) && fileMap.get(file).indexOf(word) === -1)
+          fileMap.get(file).push(word);
+        else fileMap.set(file, [word]);
+      });
+    });
+
+    // now check if the files don't contain excluded terms
+    const results = [];
+    for (const [file, wordList] of fileMap) {
+      // check if all requirements are matched
+
+      // as search terms with length < 3 are discarded
+      const filteredTermCount = [...searchTerms].filter(
+        (term) => term.length > 2
+      ).length;
+      if (
+        wordList.length !== searchTerms.size &&
+        wordList.length !== filteredTermCount
+      )
+        continue;
+
+      // ensure that none of the excluded terms is in the search result
+      if (
+        [...excludedTerms].some(
+          (term) =>
+            terms[term] === file ||
+            titleTerms[term] === file ||
+            (terms[term] || []).includes(file) ||
+            (titleTerms[term] || []).includes(file)
+        )
+      )
+        break;
+
+      // select one (max) score for the file.
+      const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w]));
+      // add result to the result list
+      results.push([
+        docNames[file],
+        titles[file],
+        "",
+        null,
+        score,
+        filenames[file],
+      ]);
+    }
+    return results;
+  },
+
+  /**
+   * helper function to return a node containing the
+   * search summary for a given text. keywords is a list
+   * of stemmed words.
+   */
+  makeSearchSummary: (htmlText, keywords) => {
+    const text = Search.htmlToText(htmlText);
+    if (text === "") return null;
+
+    const textLower = text.toLowerCase();
+    const actualStartPosition = [...keywords]
+      .map((k) => textLower.indexOf(k.toLowerCase()))
+      .filter((i) => i > -1)
+      .slice(-1)[0];
+    const startWithContext = Math.max(actualStartPosition - 120, 0);
+
+    const top = startWithContext === 0 ? "" : "...";
+    const tail = startWithContext + 240 < text.length ? "..." : "";
+
+    let summary = document.createElement("p");
+    summary.classList.add("context");
+    summary.textContent = top + text.substr(startWithContext, 240).trim() + tail;
+
+    return summary;
+  },
+};
+
+_ready(Search.init);
diff --git a/_static/sphinx_highlight.js b/_static/sphinx_highlight.js
new file mode 100644
index 00000000..8a96c69a
--- /dev/null
+++ b/_static/sphinx_highlight.js
@@ -0,0 +1,154 @@
+/* Highlighting utilities for Sphinx HTML documentation. */
+"use strict";
+
+const SPHINX_HIGHLIGHT_ENABLED = true
+
+/**
+ * highlight a given string on a node by wrapping it in
+ * span elements with the given class name.
+ */
+const _highlight = (node, addItems, text, className) => {
+  if (node.nodeType === Node.TEXT_NODE) {
+    const val = node.nodeValue;
+    const parent = node.parentNode;
+    const pos = val.toLowerCase().indexOf(text);
+    if (
+      pos >= 0 &&
+      !parent.classList.contains(className) &&
+      !parent.classList.contains("nohighlight")
+    ) {
+      let span;
+
+      const closestNode = parent.closest("body, svg, foreignObject");
+      const isInSVG = closestNode && closestNode.matches("svg");
+      if (isInSVG) {
+        span = document.createElementNS("http://www.w3.org/2000/svg", "tspan");
+      } else {
+        span = document.createElement("span");
+        span.classList.add(className);
+      }
+
+      span.appendChild(document.createTextNode(val.substr(pos, text.length)));
+      const rest = document.createTextNode(val.substr(pos + text.length));
+      parent.insertBefore(
+        span,
+        parent.insertBefore(
+          rest,
+          node.nextSibling
+        )
+      );
+      node.nodeValue = val.substr(0, pos);
+      /* There may be more occurrences of search term in this node. So call this
+       * function recursively on the remaining fragment.
+       */
+      _highlight(rest, addItems, text, className);
+
+      if (isInSVG) {
+        const rect = document.createElementNS(
+          "http://www.w3.org/2000/svg",
+          "rect"
+        );
+        const bbox = parent.getBBox();
+        rect.x.baseVal.value = bbox.x;
+        rect.y.baseVal.value = bbox.y;
+        rect.width.baseVal.value = bbox.width;
+        rect.height.baseVal.value = bbox.height;
+        rect.setAttribute("class", className);
+        addItems.push({ parent: parent, target: rect });
+      }
+    }
+  } else if (node.matches && !node.matches("button, select, textarea")) {
+    node.childNodes.forEach((el) => _highlight(el, addItems, text, className));
+  }
+};
+const _highlightText = (thisNode, text, className) => {
+  let addItems = [];
+  _highlight(thisNode, addItems, text, className);
+  addItems.forEach((obj) =>
+    obj.parent.insertAdjacentElement("beforebegin", obj.target)
+  );
+};
+
+/**
+ * Small JavaScript module for the documentation.
+ */
+const SphinxHighlight = {
+
+  /**
+   * highlight the search words provided in localstorage in the text
+   */
+  highlightSearchWords: () => {
+    if (!SPHINX_HIGHLIGHT_ENABLED) return;  // bail if no highlight
+
+    // get and clear terms from localstorage
+    const url = new URL(window.location);
+    const highlight =
+        localStorage.getItem("sphinx_highlight_terms")
+        || url.searchParams.get("highlight")
+        || "";
+    localStorage.removeItem("sphinx_highlight_terms")
+    url.searchParams.delete("highlight");
+    window.history.replaceState({}, "", url);
+
+    // get individual terms from highlight string
+    const terms = highlight.toLowerCase().split(/\s+/).filter(x => x);
+    if (terms.length === 0) return; // nothing to do
+
+    // There should never be more than one element matching "div.body"
+    const divBody = document.querySelectorAll("div.body");
+    const body = divBody.length ? divBody[0] : document.querySelector("body");
+    window.setTimeout(() => {
+      terms.forEach((term) => _highlightText(body, term, "highlighted"));
+    }, 10);
+
+    const searchBox = document.getElementById("searchbox");
+    if (searchBox === null) return;
+    searchBox.appendChild(
+      document
+        .createRange()
+        .createContextualFragment(
+          '<p class="highlight-link">' +
+            '<a href="javascript:SphinxHighlight.hideSearchWords()">' +
+            _("Hide Search Matches") +
+            "</a></p>"
+        )
+    );
+  },
+
+  /**
+   * helper function to hide the search marks again
+   */
+  hideSearchWords: () => {
+    document
+      .querySelectorAll("#searchbox .highlight-link")
+      .forEach((el) => el.remove());
+    document
+      .querySelectorAll("span.highlighted")
+      .forEach((el) => el.classList.remove("highlighted"));
+    localStorage.removeItem("sphinx_highlight_terms")
+  },
+
+  initEscapeListener: () => {
+    // only install a listener if it is really needed
+    if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return;
+
+    document.addEventListener("keydown", (event) => {
+      // bail for input elements
+      if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return;
+      // bail with special keys
+      if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return;
+      if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) {
+        SphinxHighlight.hideSearchWords();
+        event.preventDefault();
+      }
+    });
+  },
+};
+
+_ready(() => {
+  /* Do not call highlightSearchWords() when we are on the search page.
+   * It will highlight words from the *previous* search query.
+   */
+  if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords();
+  SphinxHighlight.initEscapeListener();
+});
diff --git a/algorithms.html b/algorithms.html
new file mode 100644
index 00000000..90a3677d
--- /dev/null
+++ b/algorithms.html
@@ -0,0 +1,134 @@
+<!DOCTYPE html>
+<html class="writer-html5" lang="en" data-content_root="./">
+<head>
+  <meta charset="utf-8" /><meta name="viewport" content="width=device-width, initial-scale=1" />
+
+  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+  <title>Algorithms &mdash; qlasskit  documentation</title>
+      <link rel="stylesheet" type="text/css" href="_static/pygments.css?v=68902938" />
+      <link rel="stylesheet" type="text/css" href="_static/css/theme.css?v=19f00094" />
+      <link rel="stylesheet" type="text/css" href="_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css" />
+      <link rel="stylesheet" type="text/css" href="_static/dark_mode_css/general.css?v=c0a7eb24" />
+      <link rel="stylesheet" type="text/css" href="_static/dark_mode_css/dark.css?v=70edf1c7" />
+
+  
+  <!--[if lt IE 9]>
+    <script src="_static/js/html5shiv.min.js"></script>
+  <![endif]-->
+  
+        <script src="_static/jquery.js?v=5d32c60e"></script>
+        <script src="_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
+        <script src="_static/documentation_options.js?v=5929fcd5"></script>
+        <script src="_static/doctools.js?v=888ff710"></script>
+        <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
+        <script src="_static/dark_mode_js/default_light.js?v=c2e647ce"></script>
+        <script src="_static/dark_mode_js/theme_switcher.js?v=358d3910"></script>
+    <script src="_static/js/theme.js"></script>
+    <link rel="index" title="Index" href="genindex.html" />
+    <link rel="search" title="Search" href="search.html" />
+    <link rel="next" title="API" href="api.html" />
+    <link rel="prev" title="Supported python subset" href="supported.html" /> 
+</head>
+
+<body class="wy-body-for-nav"> 
+  <div class="wy-grid-for-nav">
+    <nav data-toggle="wy-nav-shift" class="wy-nav-side">
+      <div class="wy-side-scroll">
+        <div class="wy-side-nav-search" >
+
+          
+          
+          <a href="index.html" class="icon icon-home">
+            qlasskit
+          </a>
+<div role="search">
+  <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
+    <input type="hidden" name="check_keywords" value="yes" />
+    <input type="hidden" name="area" value="default" />
+  </form>
+</div>
+        </div><div class="wy-menu wy-menu-vertical" data-spy="affix" role="navigation" aria-label="Navigation menu">
+              <p class="caption" role="heading"><span class="caption-text">Qlasskit</span></p>
+<ul class="current">
+<li class="toctree-l1"><a class="reference internal" href="quickstart.html">Quickstart</a></li>
+<li class="toctree-l1"><a class="reference internal" href="how_it_works.html">How it works</a></li>
+<li class="toctree-l1"><a class="reference internal" href="supported.html">Supported python subset</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Algorithms</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="#grover-search">Grover search</a></li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="api.html">API</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_subset.html">Grover search: subset problem</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_hash.html">Grover search: hash function preimage attack</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_sudoku.html">Grover search: sudoku solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_unitary_of_f.html">Unitary of qlasskit function</a></li>
+</ul>
+
+        </div>
+      </div>
+    </nav>
+
+    <section data-toggle="wy-nav-shift" class="wy-nav-content-wrap"><nav class="wy-nav-top" aria-label="Mobile navigation menu" >
+          <i data-toggle="wy-nav-top" class="fa fa-bars"></i>
+          <a href="index.html">qlasskit</a>
+      </nav>
+
+      <div class="wy-nav-content">
+        <div class="rst-content">
+          <div role="navigation" aria-label="Page navigation">
+  <ul class="wy-breadcrumbs">
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+      <li class="breadcrumb-item active">Algorithms</li>
+      <li class="wy-breadcrumbs-aside">
+            <a href="_sources/algorithms.rst.txt" rel="nofollow"> View page source</a>
+      </li>
+  </ul>
+  <hr/>
+</div>
+          <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
+           <div itemprop="articleBody">
+             
+  <section id="algorithms">
+<h1>Algorithms<a class="headerlink" href="#algorithms" title="Link to this heading"></a></h1>
+<section id="grover-search">
+<h2>Grover search<a class="headerlink" href="#grover-search" title="Link to this heading"></a></h2>
+</section>
+</section>
+
+
+           </div>
+          </div>
+          <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
+        <a href="supported.html" class="btn btn-neutral float-left" title="Supported python subset" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
+        <a href="api.html" class="btn btn-neutral float-right" title="API" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right" aria-hidden="true"></span></a>
+    </div>
+
+  <hr/>
+
+  <div role="contentinfo">
+    <p>&#169; Copyright 2023, Davide Gessa (dakk).</p>
+  </div>
+
+  Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a
+    <a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
+    provided by <a href="https://readthedocs.org">Read the Docs</a>.
+   
+
+</footer>
+        </div>
+      </div>
+    </section>
+  </div>
+  <script>
+      jQuery(function () {
+          SphinxRtdTheme.Navigation.enable(true);
+      });
+  </script> 
+
+</body>
+</html>
\ No newline at end of file
diff --git a/api.html b/api.html
new file mode 100644
index 00000000..33f42928
--- /dev/null
+++ b/api.html
@@ -0,0 +1,166 @@
+<!DOCTYPE html>
+<html class="writer-html5" lang="en" data-content_root="./">
+<head>
+  <meta charset="utf-8" /><meta name="viewport" content="width=device-width, initial-scale=1" />
+
+  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+  <title>API &mdash; qlasskit  documentation</title>
+      <link rel="stylesheet" type="text/css" href="_static/pygments.css?v=68902938" />
+      <link rel="stylesheet" type="text/css" href="_static/css/theme.css?v=19f00094" />
+      <link rel="stylesheet" type="text/css" href="_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css" />
+      <link rel="stylesheet" type="text/css" href="_static/dark_mode_css/general.css?v=c0a7eb24" />
+      <link rel="stylesheet" type="text/css" href="_static/dark_mode_css/dark.css?v=70edf1c7" />
+
+  
+  <!--[if lt IE 9]>
+    <script src="_static/js/html5shiv.min.js"></script>
+  <![endif]-->
+  
+        <script src="_static/jquery.js?v=5d32c60e"></script>
+        <script src="_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
+        <script src="_static/documentation_options.js?v=5929fcd5"></script>
+        <script src="_static/doctools.js?v=888ff710"></script>
+        <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
+        <script src="_static/dark_mode_js/default_light.js?v=c2e647ce"></script>
+        <script src="_static/dark_mode_js/theme_switcher.js?v=358d3910"></script>
+    <script src="_static/js/theme.js"></script>
+    <link rel="index" title="Index" href="genindex.html" />
+    <link rel="search" title="Search" href="search.html" />
+    <link rel="next" title="qlasskit.qlassfun.qlassf" href="generated/qlasskit.qlassfun.qlassf.html" />
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+<li class="toctree-l2"><a class="reference internal" href="generated/qlasskit.qcircuit.qcircuit.QCircuit.html">qlasskit.qcircuit.qcircuit.QCircuit</a></li>
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+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_subset.html">Grover search: subset problem</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_hash.html">Grover search: hash function preimage attack</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_sudoku.html">Grover search: sudoku solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_unitary_of_f.html">Unitary of qlasskit function</a></li>
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+  <section id="api">
+<h1>API<a class="headerlink" href="#api" title="Link to this heading"></a></h1>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><a class="reference internal" href="generated/qlasskit.qlassfun.qlassf.html#qlasskit.qlassfun.qlassf" title="qlasskit.qlassfun.qlassf"><code class="xref py py-obj docutils literal notranslate"><span class="pre">qlasskit.qlassfun.qlassf</span></code></a>(f[, types, defs, ...])</p></td>
+<td><p>Decorator / function creating a QlassF object</p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference internal" href="generated/qlasskit.qlassfun.qlassfa.html#qlasskit.qlassfun.qlassfa" title="qlasskit.qlassfun.qlassfa"><code class="xref py py-obj docutils literal notranslate"><span class="pre">qlasskit.qlassfun.qlassfa</span></code></a>([types, defs, ...])</p></td>
+<td><p>Decorator with parameters for qlassf</p></td>
+</tr>
+<tr class="row-odd"><td><p><a class="reference internal" href="generated/qlasskit.qlassfun.QlassF.html#qlasskit.qlassfun.QlassF" title="qlasskit.qlassfun.QlassF"><code class="xref py py-obj docutils literal notranslate"><span class="pre">qlasskit.qlassfun.QlassF</span></code></a>(name, original_f, ...)</p></td>
+<td><p>Class representing a qlassf function</p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference internal" href="generated/qlasskit.algorithms.qalgorithm.html#module-qlasskit.algorithms.qalgorithm" title="qlasskit.algorithms.qalgorithm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">qlasskit.algorithms.qalgorithm</span></code></a></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><a class="reference internal" href="generated/qlasskit.algorithms.grover.Grover.html#qlasskit.algorithms.grover.Grover" title="qlasskit.algorithms.grover.Grover"><code class="xref py py-obj docutils literal notranslate"><span class="pre">qlasskit.algorithms.grover.Grover</span></code></a>(oracle[, ...])</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference internal" href="generated/qlasskit.qcircuit.qcircuit.QCircuit.html#qlasskit.qcircuit.qcircuit.QCircuit" title="qlasskit.qcircuit.qcircuit.QCircuit"><code class="xref py py-obj docutils literal notranslate"><span class="pre">qlasskit.qcircuit.qcircuit.QCircuit</span></code></a>([...])</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><a class="reference internal" href="generated/qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.html#qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper" title="qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper"><code class="xref py py-obj docutils literal notranslate"><span class="pre">qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper</span></code></a>()</p></td>
+<td><p>Wrapper interface for a class containing a qcircuit</p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference internal" href="generated/qlasskit.qcircuit.gates.html#module-qlasskit.qcircuit.gates" title="qlasskit.qcircuit.gates"><code class="xref py py-obj docutils literal notranslate"><span class="pre">qlasskit.qcircuit.gates</span></code></a></p></td>
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diff --git a/example_grover.html b/example_grover.html
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+<!DOCTYPE html>
+<html class="writer-html5" lang="en" data-content_root="./">
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+<li class="toctree-l1 current"><a class="current reference internal" href="#">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_subset.html">Grover search: subset problem</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_hash.html">Grover search: hash function preimage attack</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_sudoku.html">Grover search: sudoku solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_unitary_of_f.html">Unitary of qlasskit function</a></li>
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+             
+  <section id="grover-search">
+<h1>Grover search<a class="headerlink" href="#grover-search" title="Link to this heading"></a></h1>
+<p>We define a function named <code class="docutils literal notranslate"><span class="pre">and_all</span></code> that returns <code class="docutils literal notranslate"><span class="pre">True</span></code> iff all the element of an input list <code class="docutils literal notranslate"><span class="pre">a_list</span></code> are <code class="docutils literal notranslate"><span class="pre">True</span></code>. We want to use a Grover search to find the input value that led to a <code class="docutils literal notranslate"><span class="pre">True</span></code> result of the function.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qlasskit</span> <span class="kn">import</span> <span class="n">qlassf</span><span class="p">,</span> <span class="n">Qlist</span><span class="p">,</span> <span class="n">Qint2</span>
+
+<span class="nd">@qlassf</span>
+<span class="k">def</span> <span class="nf">and_all</span><span class="p">(</span><span class="n">a_list</span><span class="p">:</span> <span class="n">Qlist</span><span class="p">[</span><span class="nb">bool</span><span class="p">,</span> <span class="mi">4</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
+    <span class="n">r</span> <span class="o">=</span> <span class="kc">True</span>
+    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">a_list</span><span class="p">:</span>
+        <span class="n">r</span> <span class="o">=</span> <span class="n">r</span> <span class="ow">and</span> <span class="n">i</span>
+    <span class="k">return</span> <span class="n">r</span>           
+</pre></div>
+</div>
+</div>
+</div>
+<p>The qlasskit compiler will produce an optimized quantum circuit performing the given function.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">and_all</span><span class="o">.</span><span class="n">export</span><span class="p">(</span><span class="s1">&#39;qiskit&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="s1">&#39;mpl&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/site-packages/qiskit/visualization/circuit/matplotlib.py:266: FutureWarning: The default matplotlib drawer scheme will be changed to &quot;iqp&quot; in a following release. To silence this warning, specify the current default explicitly as style=&quot;clifford&quot;, or the new default as style=&quot;iqp&quot;.
+  self._style, def_font_ratio = load_style(self._style)
+</pre></div>
+</div>
+<img alt="_images/44c9a3aa43eda23fe096518b175fdade8ee74a3e2c36a0a34f565ca369046c0b.png" src="_images/44c9a3aa43eda23fe096518b175fdade8ee74a3e2c36a0a34f565ca369046c0b.png" />
+</div>
+</div>
+<p>We now can use our quantum function as an oracle for a Grover search. For instance, we want to find the input value that yeld to a <code class="docutils literal notranslate"><span class="pre">True</span></code> value of the function:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qlasskit.algorithms</span> <span class="kn">import</span> <span class="n">Grover</span>
+
+<span class="n">q_algo</span> <span class="o">=</span> <span class="n">Grover</span><span class="p">(</span><span class="n">and_all</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Qlasskit prepares the quantum circuit for the Grover search:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">qc</span> <span class="o">=</span> <span class="n">q_algo</span><span class="o">.</span><span class="n">export</span><span class="p">(</span><span class="s1">&#39;qiskit&#39;</span><span class="p">)</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="s1">&#39;mpl&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<img alt="_images/e3c3e1af20988afbd97c6296fc6554b3f8fe2c6a40f0e173027e03f2e4b29075.png" src="_images/e3c3e1af20988afbd97c6296fc6554b3f8fe2c6a40f0e173027e03f2e4b29075.png" />
+</div>
+</div>
+<p>Now we can use our prefered framework and simulator for sampling the result; this is an example using <code class="docutils literal notranslate"><span class="pre">qiskit</span></code> with <code class="docutils literal notranslate"><span class="pre">aer_simulator</span></code>.</p>
+<p>The <code class="docutils literal notranslate"><span class="pre">Grover</span></code> class, along with all circuit wrappers in qlasskit, provides utilities to encode inputs and decode outputs from a quantum circuit using the high level type definition. In the output histogram, it’s now evident that the input leading to a <code class="docutils literal notranslate"><span class="pre">True</span></code> result in the <code class="docutils literal notranslate"><span class="pre">and_all</span></code> function is a list where all elements are set to <code class="docutils literal notranslate"><span class="pre">True</span></code>, aligning with our expectations.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qiskit</span> <span class="kn">import</span> <span class="n">Aer</span><span class="p">,</span> <span class="n">QuantumCircuit</span><span class="p">,</span> <span class="n">transpile</span>
+<span class="kn">from</span> <span class="nn">qiskit.visualization</span> <span class="kn">import</span> <span class="n">plot_histogram</span>
+
+<span class="n">qc</span><span class="o">.</span><span class="n">measure_all</span><span class="p">()</span>
+<span class="n">simulator</span> <span class="o">=</span> <span class="n">Aer</span><span class="o">.</span><span class="n">get_backend</span><span class="p">(</span><span class="s2">&quot;aer_simulator&quot;</span><span class="p">)</span>
+<span class="n">circ</span> <span class="o">=</span> <span class="n">transpile</span><span class="p">(</span><span class="n">qc</span><span class="p">,</span> <span class="n">simulator</span><span class="p">)</span>
+<span class="n">result</span> <span class="o">=</span> <span class="n">simulator</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">circ</span><span class="p">)</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>
+<span class="n">counts</span> <span class="o">=</span> <span class="n">result</span><span class="o">.</span><span class="n">get_counts</span><span class="p">(</span><span class="n">circ</span><span class="p">)</span>
+
+<span class="n">counts_readable</span> <span class="o">=</span> <span class="n">q_algo</span><span class="o">.</span><span class="n">decode_counts</span><span class="p">(</span><span class="n">counts</span><span class="p">)</span>
+<span class="n">plot_histogram</span><span class="p">(</span><span class="n">counts_readable</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<img alt="_images/7a0f3cedf6e4a1650b16511d1682a30006e6d7c7a06a8f5c9c6bb427bb630934.png" src="_images/7a0f3cedf6e4a1650b16511d1682a30006e6d7c7a06a8f5c9c6bb427bb630934.png" />
+</div>
+</div>
+</section>
+
+
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+  <section id="grover-search-hash-function-preimage-attack">
+<h1>Grover search: hash function preimage attack<a class="headerlink" href="#grover-search-hash-function-preimage-attack" title="Link to this heading"></a></h1>
+<p>In the ever-evolving landscape of cybersecurity, the advent of quantum computing presents both an extraordinary opportunity and an unprecedented challenge. In this notebook we exploit a Grover Search to perform a preimage attack on a toy hash function.</p>
+<p>A preimage attack on a cryptographic hash function <code class="docutils literal notranslate"><span class="pre">h(m)</span></code> tries to find a message <code class="docutils literal notranslate"><span class="pre">m</span></code> that has a specific hash value. Using qlasskit it is easy to write an hash function like the following <code class="docutils literal notranslate"><span class="pre">hash_simp</span></code>:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qlasskit</span> <span class="kn">import</span> <span class="n">qlassf</span><span class="p">,</span> <span class="n">Qint4</span><span class="p">,</span> <span class="n">Qint8</span><span class="p">,</span> <span class="n">Qlist</span>
+
+<span class="nd">@qlassf</span>
+<span class="k">def</span> <span class="nf">hash_simp</span><span class="p">(</span><span class="n">m</span><span class="p">:</span> <span class="n">Qlist</span><span class="p">[</span><span class="n">Qint4</span><span class="p">,</span> <span class="mi">2</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">Qint8</span><span class="p">:</span>
+    <span class="n">hv</span> <span class="o">=</span> <span class="mi">0</span>
+    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">m</span><span class="p">:</span>
+        <span class="n">hv</span> <span class="o">=</span> <span class="p">((</span><span class="n">hv</span> <span class="o">&lt;&lt;</span> <span class="mi">4</span><span class="p">)</span> <span class="o">^</span> <span class="p">(</span><span class="n">hv</span> <span class="o">&gt;&gt;</span> <span class="mi">1</span><span class="p">)</span> <span class="o">^</span> <span class="n">i</span><span class="p">)</span> <span class="o">&amp;</span> <span class="mh">0xff</span>
+
+    <span class="k">return</span> <span class="n">hv</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Thanks to the fact that qlasskit function are standard python functions, we can call the <code class="docutils literal notranslate"><span class="pre">original_f</span></code> to perform some kind of analysis on the hash function. Since the input space is tiny (it is a toy hash function), we can detect if the hash function is uniform (if it maps equally to the output space).</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">collections</span> <span class="kn">import</span> <span class="n">Counter</span>
+
+<span class="n">d</span> <span class="o">=</span> <span class="n">Counter</span><span class="p">(</span><span class="nb">hex</span><span class="p">(</span><span class="n">hash_simp</span><span class="o">.</span><span class="n">original_f</span><span class="p">((</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)))</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">2</span><span class="o">**</span><span class="mi">4</span><span class="p">)</span> <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">2</span><span class="o">**</span><span class="mi">4</span><span class="p">))</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Hash function output space:&#39;</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">d</span><span class="p">))</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Hash function output space: 256
+</pre></div>
+</div>
+</div>
+</div>
+<p>We got that <code class="docutils literal notranslate"><span class="pre">hash_simp</span></code> is following an uniform distribution.</p>
+<p>We now can use our quantum function as an oracle for a Grover search, in order to find which input maps to the value <code class="docutils literal notranslate"><span class="pre">ca</span></code>.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qlasskit.algorithms</span> <span class="kn">import</span> <span class="n">Grover</span>
+
+<span class="n">q_algo</span> <span class="o">=</span> <span class="n">Grover</span><span class="p">(</span><span class="n">hash_simp</span><span class="p">,</span> <span class="n">Qint8</span><span class="p">(</span><span class="mh">0xca</span><span class="p">))</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Now we can use our prefered framework and simulator for sampling the result; this is an example using <code class="docutils literal notranslate"><span class="pre">qiskit</span></code> with <code class="docutils literal notranslate"><span class="pre">aer_simulator</span></code>.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qiskit</span> <span class="kn">import</span> <span class="n">Aer</span><span class="p">,</span> <span class="n">QuantumCircuit</span><span class="p">,</span> <span class="n">transpile</span>
+<span class="kn">from</span> <span class="nn">qiskit.visualization</span> <span class="kn">import</span> <span class="n">plot_histogram</span>
+
+<span class="n">qc</span> <span class="o">=</span> <span class="n">q_algo</span><span class="o">.</span><span class="n">export</span><span class="p">(</span><span class="s1">&#39;qiskit&#39;</span><span class="p">)</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">measure_all</span><span class="p">()</span>
+<span class="n">simulator</span> <span class="o">=</span> <span class="n">Aer</span><span class="o">.</span><span class="n">get_backend</span><span class="p">(</span><span class="s2">&quot;aer_simulator&quot;</span><span class="p">)</span>
+<span class="n">circ</span> <span class="o">=</span> <span class="n">transpile</span><span class="p">(</span><span class="n">qc</span><span class="p">,</span> <span class="n">simulator</span><span class="p">)</span>
+<span class="n">result</span> <span class="o">=</span> <span class="n">simulator</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">circ</span><span class="p">)</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>
+<span class="n">counts</span> <span class="o">=</span> <span class="n">result</span><span class="o">.</span><span class="n">get_counts</span><span class="p">(</span><span class="n">circ</span><span class="p">)</span>
+
+<span class="n">counts_readable</span> <span class="o">=</span> <span class="n">q_algo</span><span class="o">.</span><span class="n">decode_counts</span><span class="p">(</span><span class="n">counts</span><span class="p">,</span> <span class="n">discard_lower</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
+<span class="n">plot_histogram</span><span class="p">(</span><span class="n">counts_readable</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<img alt="_images/d19805380f7379838dd2610658b919af97837aa5f3ca65e2ac7eecb6b323453f.png" src="_images/d19805380f7379838dd2610658b919af97837aa5f3ca65e2ac7eecb6b323453f.png" />
+</div>
+</div>
+<p>We now double check using <code class="docutils literal notranslate"><span class="pre">original_f</span></code>; calling it with the tuple <code class="docutils literal notranslate"><span class="pre">(12,12)</span></code> must result in the hash value <code class="docutils literal notranslate"><span class="pre">0xca</span></code>.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="nb">hex</span><span class="p">(</span><span class="n">hash_simp</span><span class="o">.</span><span class="n">original_f</span><span class="p">((</span><span class="mi">12</span><span class="p">,</span><span class="mi">12</span><span class="p">))))</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0xca
+</pre></div>
+</div>
+</div>
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+  <section id="grover-search-subset-problem">
+<h1>Grover search: subset problem<a class="headerlink" href="#grover-search-subset-problem" title="Link to this heading"></a></h1>
+<p>We define a function named <code class="docutils literal notranslate"><span class="pre">subset_sum(i,j)</span></code> that returns the sum of the elements <code class="docutils literal notranslate"><span class="pre">i</span></code> and <code class="docutils literal notranslate"><span class="pre">j</span></code> of a list <code class="docutils literal notranslate"><span class="pre">l</span></code>. We want to use a Grover search to find which <code class="docutils literal notranslate"><span class="pre">i</span></code> <code class="docutils literal notranslate"><span class="pre">j</span></code> combination led to a given value.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qlasskit</span> <span class="kn">import</span> <span class="n">qlassf</span><span class="p">,</span> <span class="n">Qint2</span><span class="p">,</span> <span class="n">Qint3</span>
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Tuple</span>
+
+<span class="nd">@qlassf</span>
+<span class="k">def</span> <span class="nf">subset_sum</span><span class="p">(</span><span class="n">ii</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">Qint2</span><span class="p">,</span> <span class="n">Qint2</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">Qint3</span><span class="p">:</span>
+    <span class="n">l</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]</span>
+    <span class="k">return</span> <span class="n">l</span><span class="p">[</span><span class="n">ii</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span> <span class="o">+</span> <span class="n">l</span><span class="p">[</span><span class="n">ii</span><span class="p">[</span><span class="mi">1</span><span class="p">]]</span> <span class="k">if</span> <span class="n">ii</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">!=</span> <span class="n">ii</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">else</span> <span class="mi">0</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>We now can use our quantum function as an oracle for a Grover search. For instance, we want to find the input value that produce the value <code class="docutils literal notranslate"><span class="pre">7</span></code>. Since we know that there are at least two result (<code class="docutils literal notranslate"><span class="pre">(i,j)</span></code> and <code class="docutils literal notranslate"><span class="pre">(j,i)</span></code>), we set <code class="docutils literal notranslate"><span class="pre">n_matching=2</span></code>.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qlasskit.algorithms</span> <span class="kn">import</span> <span class="n">Grover</span>
+
+<span class="n">q_algo</span> <span class="o">=</span> <span class="n">Grover</span><span class="p">(</span><span class="n">subset_sum</span><span class="p">,</span> <span class="n">Qint3</span><span class="p">(</span><span class="mi">7</span><span class="p">),</span> <span class="n">n_matching</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Now we can use our prefered framework and simulator for sampling the result; this is an example using <code class="docutils literal notranslate"><span class="pre">qiskit</span></code> with <code class="docutils literal notranslate"><span class="pre">aer_simulator</span></code>.</p>
+<p>In the output histogram, it’s now evident that the input leading to a value of <code class="docutils literal notranslate"><span class="pre">7</span></code> are the tuples <code class="docutils literal notranslate"><span class="pre">(1,2)</span></code> and <code class="docutils literal notranslate"><span class="pre">(2,1)</span></code> (5+2 and 2+5), aligning with our expectations.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qiskit</span> <span class="kn">import</span> <span class="n">Aer</span><span class="p">,</span> <span class="n">QuantumCircuit</span><span class="p">,</span> <span class="n">transpile</span>
+<span class="kn">from</span> <span class="nn">qiskit.visualization</span> <span class="kn">import</span> <span class="n">plot_histogram</span>
+
+<span class="n">qc</span> <span class="o">=</span> <span class="n">q_algo</span><span class="o">.</span><span class="n">export</span><span class="p">(</span><span class="s1">&#39;qiskit&#39;</span><span class="p">)</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">measure_all</span><span class="p">()</span>
+<span class="n">simulator</span> <span class="o">=</span> <span class="n">Aer</span><span class="o">.</span><span class="n">get_backend</span><span class="p">(</span><span class="s2">&quot;aer_simulator&quot;</span><span class="p">)</span>
+<span class="n">circ</span> <span class="o">=</span> <span class="n">transpile</span><span class="p">(</span><span class="n">qc</span><span class="p">,</span> <span class="n">simulator</span><span class="p">)</span>
+<span class="n">result</span> <span class="o">=</span> <span class="n">simulator</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">circ</span><span class="p">)</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>
+<span class="n">counts</span> <span class="o">=</span> <span class="n">result</span><span class="o">.</span><span class="n">get_counts</span><span class="p">(</span><span class="n">circ</span><span class="p">)</span>
+
+<span class="n">counts_readable</span> <span class="o">=</span> <span class="n">q_algo</span><span class="o">.</span><span class="n">decode_counts</span><span class="p">(</span><span class="n">counts</span><span class="p">)</span>
+<span class="n">plot_histogram</span><span class="p">(</span><span class="n">counts_readable</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<img alt="_images/6f943927f4e7f022046baf725bd97d0234b6d284f35b8a8d70abbd49ae18d2e5.png" src="_images/6f943927f4e7f022046baf725bd97d0234b6d284f35b8a8d70abbd49ae18d2e5.png" />
+</div>
+</div>
+</section>
+
+
+           </div>
+          </div>
+          <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
+        <a href="example_grover.html" class="btn btn-neutral float-left" title="Grover search" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
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+    </div>
+
+  <hr/>
+
+  <div role="contentinfo">
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+  </div>
+
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+          SphinxRtdTheme.Navigation.enable(true);
+      });
+  </script> 
+
+</body>
+</html>
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+<li class="toctree-l1"><a class="reference internal" href="supported.html">Supported python subset</a></li>
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+</ul>
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+             
+  <section id="grover-search-sudoku-solver">
+<h1>Grover search: sudoku solver<a class="headerlink" href="#grover-search-sudoku-solver" title="Link to this heading"></a></h1>
+<p>In this example we are going to solve a sudoku puzzle. Since we have few qubits, we need to simplify the puzzle and so we use a 2x2 matrix where a valid solution is when in every row and every column there are no repeated values (<code class="docutils literal notranslate"><span class="pre">0</span></code> or <code class="docutils literal notranslate"><span class="pre">1</span></code>). We encode these xor-ing the values for each row and column.
+Since we want a specific solution, we add a constraint <code class="docutils literal notranslate"><span class="pre">constr</span></code>: we want the <code class="docutils literal notranslate"><span class="pre">[0][0]</span></code> element to be <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p>
+<p>We instantiate the <code class="docutils literal notranslate"><span class="pre">Grover</span></code> algorithm without value, since sudoku_check is already an oracle.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qlasskit</span> <span class="kn">import</span> <span class="n">qlassf</span><span class="p">,</span> <span class="n">Qint2</span><span class="p">,</span> <span class="n">Qint4</span><span class="p">,</span> <span class="n">Qmatrix</span>
+<span class="kn">from</span> <span class="nn">qlasskit.algorithms</span> <span class="kn">import</span> <span class="n">Grover</span>
+
+<span class="nd">@qlassf</span>
+<span class="k">def</span> <span class="nf">sudoku_check</span><span class="p">(</span><span class="n">m</span><span class="p">:</span> <span class="n">Qmatrix</span><span class="p">[</span><span class="nb">bool</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
+    <span class="n">constr</span> <span class="o">=</span> <span class="n">m</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+    <span class="n">sub0</span> <span class="o">=</span> <span class="p">(</span><span class="n">m</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">^</span> <span class="n">m</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">])</span>
+    <span class="n">sub1</span> <span class="o">=</span> <span class="p">(</span><span class="n">m</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">^</span> <span class="n">m</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="mi">1</span><span class="p">])</span>    
+    <span class="n">sub2</span> <span class="o">=</span> <span class="p">(</span><span class="n">m</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">^</span> <span class="n">m</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="mi">0</span><span class="p">])</span>
+    <span class="n">sub3</span> <span class="o">=</span> <span class="p">(</span><span class="n">m</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span> <span class="o">^</span> <span class="n">m</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="mi">1</span><span class="p">])</span>
+    <span class="k">return</span> <span class="n">sub0</span> <span class="ow">and</span> <span class="n">sub1</span> <span class="ow">and</span> <span class="n">sub2</span> <span class="ow">and</span> <span class="n">sub3</span> <span class="ow">and</span> <span class="n">constr</span>
+
+<span class="n">q_algo</span> <span class="o">=</span> <span class="n">Grover</span><span class="p">(</span><span class="n">sudoku_check</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>Now we can use our prefered framework and simulator for sampling the result; this is an example using <code class="docutils literal notranslate"><span class="pre">qiskit</span></code> with <code class="docutils literal notranslate"><span class="pre">aer_simulator</span></code>.</p>
+<p>We obtain that the solution for this puzzle is the matrix <code class="docutils literal notranslate"><span class="pre">[[True,</span> <span class="pre">False],</span> <span class="pre">[False,</span> <span class="pre">True]]</span></code>.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qiskit</span> <span class="kn">import</span> <span class="n">Aer</span><span class="p">,</span> <span class="n">QuantumCircuit</span><span class="p">,</span> <span class="n">transpile</span>
+<span class="kn">from</span> <span class="nn">qiskit.visualization</span> <span class="kn">import</span> <span class="n">plot_histogram</span>
+
+<span class="n">qc</span> <span class="o">=</span> <span class="n">q_algo</span><span class="o">.</span><span class="n">export</span><span class="p">(</span><span class="s1">&#39;qiskit&#39;</span><span class="p">)</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">measure_all</span><span class="p">()</span>
+<span class="n">simulator</span> <span class="o">=</span> <span class="n">Aer</span><span class="o">.</span><span class="n">get_backend</span><span class="p">(</span><span class="s2">&quot;aer_simulator&quot;</span><span class="p">)</span>
+<span class="n">circ</span> <span class="o">=</span> <span class="n">transpile</span><span class="p">(</span><span class="n">qc</span><span class="p">,</span> <span class="n">simulator</span><span class="p">)</span>
+<span class="n">result</span> <span class="o">=</span> <span class="n">simulator</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">circ</span><span class="p">)</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>
+<span class="n">counts</span> <span class="o">=</span> <span class="n">result</span><span class="o">.</span><span class="n">get_counts</span><span class="p">(</span><span class="n">circ</span><span class="p">)</span>
+
+<span class="n">counts_readable</span> <span class="o">=</span> <span class="n">q_algo</span><span class="o">.</span><span class="n">decode_counts</span><span class="p">(</span><span class="n">counts</span><span class="p">,</span> <span class="n">discard_lower</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
+<span class="n">plot_histogram</span><span class="p">(</span><span class="n">counts_readable</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<img alt="_images/ea41932c680a118cee625c379616f3eb2bc1845c772fc3b4c9431f50c80e16ed.png" src="_images/ea41932c680a118cee625c379616f3eb2bc1845c772fc3b4c9431f50c80e16ed.png" />
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+
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+  <section id="unitary-of-qlasskit-function">
+<h1>Unitary of qlasskit function<a class="headerlink" href="#unitary-of-qlasskit-function" title="Link to this heading"></a></h1>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qiskit</span> <span class="kn">import</span> <span class="n">Aer</span><span class="p">,</span> <span class="n">QuantumCircuit</span><span class="p">,</span> <span class="n">transpile</span><span class="p">,</span> <span class="n">execute</span>
+<span class="kn">from</span> <span class="nn">qiskit.visualization</span> <span class="kn">import</span> <span class="n">array_to_latex</span>
+<span class="kn">from</span> <span class="nn">qlasskit</span> <span class="kn">import</span> <span class="n">qlassf</span>
+
+<span class="nd">@qlassf</span>
+<span class="k">def</span> <span class="nf">f</span><span class="p">(</span><span class="n">a</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="nb">bool</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
+    <span class="k">return</span> <span class="n">a</span> <span class="o">^</span> <span class="p">(</span><span class="ow">not</span> <span class="n">b</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="si">{</span><span class="n">f</span><span class="si">}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
+
+<span class="n">qc</span> <span class="o">=</span> <span class="n">QuantumCircuit</span><span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="n">num_qubits</span><span class="p">,</span> <span class="n">f</span><span class="o">.</span><span class="n">num_qubits</span><span class="p">)</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="n">gate</span><span class="p">(),</span> <span class="n">f</span><span class="o">.</span><span class="n">qubits</span><span class="p">)</span>
+
+<span class="n">qc</span><span class="o">.</span><span class="n">decompose</span><span class="p">()</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="s1">&#39;mpl&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>QlassF&lt;f&gt;(a:bool, b:bool) -&gt; bool:
+	_ret = a ^ ~b
+</pre></div>
+</div>
+<img alt="_images/f988cf8271837cb1b9caf21c4d307e4857aa36b6b8b9f774cf372dec22e57051.png" src="_images/f988cf8271837cb1b9caf21c4d307e4857aa36b6b8b9f774cf372dec22e57051.png" />
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">simulator</span> <span class="o">=</span> <span class="n">Aer</span><span class="o">.</span><span class="n">get_backend</span><span class="p">(</span><span class="s1">&#39;unitary_simulator&#39;</span><span class="p">)</span>
+<span class="n">job</span> <span class="o">=</span> <span class="n">execute</span><span class="p">(</span><span class="n">qc</span><span class="p">,</span> <span class="n">simulator</span><span class="p">,</span> <span class="n">shots</span><span class="o">=</span><span class="mi">8192</span><span class="p">)</span>
+<span class="n">result</span> <span class="o">=</span> <span class="n">job</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>
+<span class="n">array_to_latex</span><span class="p">(</span><span class="n">result</span><span class="o">.</span><span class="n">get_unitary</span><span class="p">(</span><span class="n">qc</span><span class="p">,</span><span class="mi">3</span><span class="p">),</span> <span class="n">max_size</span><span class="o">=</span><span class="mi">16</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output text_latex math notranslate nohighlight">
+\[\begin{split}\begin{bmatrix}
+0 &amp; 0 &amp; 0 &amp; 0 &amp; 1 &amp; 0 &amp; 0 &amp; 0  \\
+ 0 &amp; 1 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0  \\
+ 0 &amp; 0 &amp; 1 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0  \\
+ 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 1  \\
+ 1 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0  \\
+ 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 1 &amp; 0 &amp; 0  \\
+ 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 0 &amp; 1 &amp; 0  \\
+ 0 &amp; 0 &amp; 0 &amp; 1 &amp; 0 &amp; 0 &amp; 0 &amp; 0  \\
+ \end{bmatrix}
+\end{split}\]</div>
+</div>
+</div>
+</section>
+
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+  <section id="qlasskit-algorithms-grover-grover">
+<h1>qlasskit.algorithms.grover.Grover<a class="headerlink" href="#qlasskit-algorithms-grover-grover" title="Link to this heading"></a></h1>
+<dl class="py class">
+<dt class="sig sig-object py" id="qlasskit.algorithms.grover.Grover">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">qlasskit.algorithms.grover.</span></span><span class="sig-name descname"><span class="pre">Grover</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">oracle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="qlasskit.qlassfun.QlassF.html#qlasskit.qlassfun.QlassF" title="qlasskit.qlassfun.QlassF"><span class="pre">QlassF</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">element_to_search</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Qtype</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_iterations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_matching</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#qlasskit.algorithms.grover.Grover" title="Link to this definition"></a></dt>
+<dd><dl class="py method">
+<dt class="sig sig-object py" id="qlasskit.algorithms.grover.Grover.__init__">
+<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">oracle</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="qlasskit.qlassfun.QlassF.html#qlasskit.qlassfun.QlassF" title="qlasskit.qlassfun.QlassF"><span class="pre">QlassF</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">element_to_search</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Qtype</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_iterations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_matching</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#qlasskit.algorithms.grover.Grover.__init__" title="Link to this definition"></a></dt>
+<dd><dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>oracle</strong> (<a class="reference internal" href="qlasskit.qlassfun.QlassF.html#qlasskit.qlassfun.QlassF" title="qlasskit.qlassfun.QlassF"><em>QlassF</em></a>) – our f(x) -&gt; bool that returns True if x satisfies the function or
+a generic function f(x) = y that we want to compare with element_to_search</p></li>
+<li><p><strong>element_to_search</strong> (<em>Qtype</em><em>, </em><em>optional</em>) – the element we want to search</p></li>
+<li><p><strong>n_iterations</strong> (<em>int</em><em>, </em><em>optional</em>) – force a number of iterations
+(otherwise, pi/4*sqrt(N/n_matching))</p></li>
+<li><p><strong>n_matching</strong> (<em>int</em>) – the number of expected matching values (default: 1)</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+<p class="rubric">Methods</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><a class="reference internal" href="#qlasskit.algorithms.grover.Grover.__init__" title="qlasskit.algorithms.grover.Grover.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>(oracle[, element_to_search, ...])</p></td>
+<td><p><dl class="field-list simple">
+<dt class="field-odd">param oracle<span class="colon">:</span></dt>
+<dd class="field-odd"><p>our f(x) -&gt; bool that returns True if x satisfies the function or</p>
+</dd>
+</dl>
+</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">circuit</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">decode_counts</span></code>(counts[, discard_lower])</p></td>
+<td><p>Decode data from a circuit counts dict</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">decode_output</span></code>(istr)</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">draw</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">encode_input</span></code>(*qvals)</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">export</span></code>([framework])</p></td>
+<td><p>Export the circuit to a supported framework</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">gate</span></code>([framework])</p></td>
+<td><p>Returns the gate for a specific framework</p></td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Attributes</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">input_qubits</span></code></p></td>
+<td><p>Returns the list of input qubits</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">input_size</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">num_qubits</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">output_qubits</span></code></p></td>
+<td><p>Returns the list of output qubits</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">output_size</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">qubits</span></code></p></td>
+<td><p>Returns all the qubits of the circuit</p></td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+</section>
+
+
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+<li class="toctree-l2"><a class="reference internal" href="qlasskit.qcircuit.qcircuit.QCircuit.html">qlasskit.qcircuit.qcircuit.QCircuit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.html">qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper</a></li>
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+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover_subset.html">Grover search: subset problem</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../example_unitary_of_f.html">Unitary of qlasskit function</a></li>
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+             
+  <section id="module-qlasskit.algorithms.qalgorithm">
+<span id="qlasskit-algorithms-qalgorithm"></span><h1>qlasskit.algorithms.qalgorithm<a class="headerlink" href="#module-qlasskit.algorithms.qalgorithm" title="Link to this heading"></a></h1>
+<p class="rubric">Functions</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">oraclize</span></code>(qf, element[, name])</p></td>
+<td><p>Transform a QlassF qf and an element to an oracle {f(x) = x == element}</p></td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Classes</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">QAlgorithm</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Exceptions</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">ConstantOracleException</span></code></p></td>
+<td><p></p></td>
+</tr>
+</tbody>
+</table>
+</section>
+
+
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+          </div>
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+<li class="toctree-l2"><a class="reference internal" href="qlasskit.qlassfun.QlassF.html">qlasskit.qlassfun.QlassF</a></li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.algorithms.qalgorithm.html">qlasskit.algorithms.qalgorithm</a></li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.algorithms.grover.Grover.html">qlasskit.algorithms.grover.Grover</a></li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.qcircuit.qcircuit.QCircuit.html">qlasskit.qcircuit.qcircuit.QCircuit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.html">qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper</a></li>
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+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover_subset.html">Grover search: subset problem</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../example_grover_sudoku.html">Grover search: sudoku solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../example_unitary_of_f.html">Unitary of qlasskit function</a></li>
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+  <section id="module-qlasskit.qcircuit.gates">
+<span id="qlasskit-qcircuit-gates"></span><h1>qlasskit.qcircuit.gates<a class="headerlink" href="#module-qlasskit.qcircuit.gates" title="Link to this heading"></a></h1>
+<p class="rubric">Functions</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">apply</span></code>(gate, qubits[, param])</p></td>
+<td><p></p></td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Classes</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">Barrier</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">CCX</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">CX</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">H</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">MCX</span></code>(n_controls)</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">MCtrl</span></code>(gate, n_controls)</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">NopGate</span></code>([name])</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">QControlledGate</span></code>(gate, n_controls)</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">QGate</span></code>(name[, n_qubits])</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">S</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">T</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">Toffoli</span></code></p></td>
+<td><p>alias of <code class="xref py py-class docutils literal notranslate"><span class="pre">CCX</span></code></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">X</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">Y</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">Z</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+</tbody>
+</table>
+</section>
+
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+<li class="toctree-l3"><a class="reference internal" href="#qlasskit.qcircuit.qcircuit.QCircuit"><code class="docutils literal notranslate"><span class="pre">QCircuit</span></code></a><ul>
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+  <section id="qlasskit-qcircuit-qcircuit-qcircuit">
+<h1>qlasskit.qcircuit.qcircuit.QCircuit<a class="headerlink" href="#qlasskit-qcircuit-qcircuit-qcircuit" title="Link to this heading"></a></h1>
+<dl class="py class">
+<dt class="sig sig-object py" id="qlasskit.qcircuit.qcircuit.QCircuit">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">qlasskit.qcircuit.qcircuit.</span></span><span class="sig-name descname"><span class="pre">QCircuit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_qubits</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'qc'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">native</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#qlasskit.qcircuit.qcircuit.QCircuit" title="Link to this definition"></a></dt>
+<dd><dl class="py method">
+<dt class="sig sig-object py" id="qlasskit.qcircuit.qcircuit.QCircuit.__init__">
+<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_qubits</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'qc'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">native</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#qlasskit.qcircuit.qcircuit.QCircuit.__init__" title="Link to this definition"></a></dt>
+<dd><p>Initialize a quantum circuit.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>num_qubits</strong> (<em>int</em><em>, </em><em>optional</em>) – The number of qubits in the circuit. Defaults to 0.</p>
+</dd>
+</dl>
+</dd></dl>
+
+<p class="rubric">Methods</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><a class="reference internal" href="#qlasskit.qcircuit.qcircuit.QCircuit.__init__" title="qlasskit.qcircuit.qcircuit.QCircuit.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>([num_qubits, name, native])</p></td>
+<td><p>Initialize a quantum circuit.</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">add_qubit</span></code>([name])</p></td>
+<td><p>Add a qubit to the circuit.</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">append</span></code>(gate, qubits[, param])</p></td>
+<td><p>Append a gate operation to the circuit.</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">barrier</span></code>([label])</p></td>
+<td><p>Add a barrier to the circuit</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">ccx</span></code>(w1, w2, w3)</p></td>
+<td><p>CCX gate</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">copy</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">cx</span></code>(w1, w2)</p></td>
+<td><p>CX gate</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">draw</span></code>()</p></td>
+<td><p>Draw the circuit</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">export</span></code>([mode, framework])</p></td>
+<td><p>Exports the circuit to another framework.</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_key_by_index</span></code>(i)</p></td>
+<td><p>Return the qubit name given its index</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">h</span></code>(w)</p></td>
+<td><p>H gate</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">mctrl</span></code>(g, wl, target[, param])</p></td>
+<td><p>Multi controlled gate</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">mcx</span></code>(wl, target)</p></td>
+<td><p>Multi CX gate</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">s</span></code>(w)</p></td>
+<td><p>S gate</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">t</span></code>(w)</p></td>
+<td><p>T gate</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">x</span></code>(w)</p></td>
+<td><p>X gate</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">y</span></code>(w)</p></td>
+<td><p>Y gate</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">z</span></code>(w)</p></td>
+<td><p>Z gate</p></td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Attributes</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">num_gates</span></code></p></td>
+<td><p></p></td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+</section>
+
+
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+<li class="toctree-l3"><a class="reference internal" href="#qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper"><code class="docutils literal notranslate"><span class="pre">QCircuitWrapper</span></code></a><ul>
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+<ul>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover_subset.html">Grover search: subset problem</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../example_unitary_of_f.html">Unitary of qlasskit function</a></li>
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+  <section id="qlasskit-qcircuit-qcircuitwrapper-qcircuitwrapper">
+<h1>qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper<a class="headerlink" href="#qlasskit-qcircuit-qcircuitwrapper-qcircuitwrapper" title="Link to this heading"></a></h1>
+<dl class="py class">
+<dt class="sig sig-object py" id="qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">qlasskit.qcircuit.qcircuitwrapper.</span></span><span class="sig-name descname"><span class="pre">QCircuitWrapper</span></span><a class="headerlink" href="#qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper" title="Link to this definition"></a></dt>
+<dd><p>Wrapper interface for a class containing a qcircuit</p>
+<dl class="py method">
+<dt class="sig sig-object py" id="qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.__init__">
+<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.__init__" title="Link to this definition"></a></dt>
+<dd></dd></dl>
+
+<p class="rubric">Methods</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><a class="reference internal" href="#qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.__init__" title="qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">circuit</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">decode_counts</span></code>(counts[, discard_lower])</p></td>
+<td><p>Decode data from a circuit counts dict</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">decode_output</span></code>(istr)</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">draw</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">encode_input</span></code>(*qvals)</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">export</span></code>([framework])</p></td>
+<td><p>Export the circuit to a supported framework</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">gate</span></code>([framework])</p></td>
+<td><p>Returns the gate for a specific framework</p></td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Attributes</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">input_qubits</span></code></p></td>
+<td><p>Returns the list of input qubits</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">input_size</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">num_qubits</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">output_qubits</span></code></p></td>
+<td><p>Returns the list of output qubits</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">output_size</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">qubits</span></code></p></td>
+<td><p>Returns all the qubits of the circuit</p></td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+</section>
+
+
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+  <section id="qlasskit-qlassfun-qlassf">
+<h1>qlasskit.qlassfun.QlassF<a class="headerlink" href="#qlasskit-qlassfun-qlassf" title="Link to this heading"></a></h1>
+<dl class="py class">
+<dt class="sig sig-object py" id="qlasskit.qlassfun.QlassF">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">qlasskit.qlassfun.</span></span><span class="sig-name descname"><span class="pre">QlassF</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">original_f</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">Arg</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">returns</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Arg</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Symbol</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Boolean</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#qlasskit.qlassfun.QlassF" title="Link to this definition"></a></dt>
+<dd><p>Class representing a qlassf function</p>
+<dl class="py method">
+<dt class="sig sig-object py" id="qlasskit.qlassfun.QlassF.__init__">
+<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">original_f</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">Arg</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">returns</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Arg</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Symbol</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Boolean</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#qlasskit.qlassfun.QlassF.__init__" title="Link to this definition"></a></dt>
+<dd></dd></dl>
+
+<p class="rubric">Methods</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><a class="reference internal" href="#qlasskit.qlassfun.QlassF.__init__" title="qlasskit.qlassfun.QlassF.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>(name, original_f, args, returns, exps)</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">bind</span></code>(**kwargs)</p></td>
+<td><p>Returns a new QlassF with defined params</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">circuit</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">compile</span></code>([compiler, uncompute])</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">decode_counts</span></code>(counts[, discard_lower])</p></td>
+<td><p>Decode data from a circuit counts dict</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">decode_output</span></code>(istr)</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">draw</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">encode_input</span></code>(*qvals)</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">export</span></code>([framework])</p></td>
+<td><p>Export the circuit to a supported framework</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">f</span></code>()</p></td>
+<td><p>Returns the classical python function</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">from_function</span></code>(f[, types, defs, to_compile, ...])</p></td>
+<td><p>Create a QlassF from a function or a string containing a function</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">gate</span></code>([framework])</p></td>
+<td><p>Returns the gate for a specific framework</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_logicfun</span></code>()</p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">truth_table</span></code>([max])</p></td>
+<td><p>Returns the truth table for the function using the sympy boolean for computing</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">truth_table_header</span></code>()</p></td>
+<td><p>Returns the list of string containing the truth table header</p></td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Attributes</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">input_qubits</span></code></p></td>
+<td><p>Returns the list of input qubits</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">input_size</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">num_qubits</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">output_qubits</span></code></p></td>
+<td><p>Returns the list of output qubits</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">output_size</span></code></p></td>
+<td><p>Return the size of the return type (in bits)</p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">qubits</span></code></p></td>
+<td><p>Returns all the qubits of the circuit</p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">name</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">original_f</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">args</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">returns</span></code></p></td>
+<td><p></p></td>
+</tr>
+<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">expressions</span></code></p></td>
+<td><p></p></td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+</section>
+
+
+           </div>
+          </div>
+          <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
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+<li class="toctree-l1"><a class="reference internal" href="../supported.html">Supported python subset</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../algorithms.html">Algorithms</a></li>
+<li class="toctree-l1 current"><a class="reference internal" href="../api.html">API</a><ul class="current">
+<li class="toctree-l2 current"><a class="current reference internal" href="#">qlasskit.qlassfun.qlassf</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="#qlasskit.qlassfun.qlassf"><code class="docutils literal notranslate"><span class="pre">qlassf()</span></code></a></li>
+</ul>
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+</ul>
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+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover.html">Grover search</a></li>
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+             
+  <section id="qlasskit-qlassfun-qlassf">
+<h1>qlasskit.qlassfun.qlassf<a class="headerlink" href="#qlasskit-qlassfun-qlassf" title="Link to this heading"></a></h1>
+<dl class="py function">
+<dt class="sig sig-object py" id="qlasskit.qlassfun.qlassf">
+<span class="sig-prename descclassname"><span class="pre">qlasskit.qlassfun.</span></span><span class="sig-name descname"><span class="pre">qlassf</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">f:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">~typing.Callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">types:</span> <span class="pre">~typing.List[~qlasskit.types.qtype.Qtype]</span> <span class="pre">=</span> <span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">defs:</span> <span class="pre">~typing.List[~qlasskit.qlassfun.QlassF]</span> <span class="pre">=</span> <span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">to_compile:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compiler:</span> <span class="pre">~typing.Literal['internal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">'poc3'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">'tweedledum']</span> <span class="pre">=</span> <span class="pre">'internal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bool_optimizer:</span> <span class="pre">~qlasskit.boolopt.bool_optimizer.BoolOptimizerProfile</span> <span class="pre">=</span> <span class="pre">&lt;qlasskit.boolopt.bool_optimizer.BoolOptimizerProfile</span> <span class="pre">object&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uncompute:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="qlasskit.qlassfun.QlassF.html#qlasskit.qlassfun.QlassF" title="qlasskit.qlassfun.QlassF"><span class="pre">QlassF</span></a></span></span><a class="headerlink" href="#qlasskit.qlassfun.qlassf" title="Link to this definition"></a></dt>
+<dd><p>Decorator / function creating a QlassF object</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>f</strong> (<em>Union</em><em>[</em><em>str</em><em>, </em><em>Callable</em><em>]</em>) – the function to be parsed, as a str code or callable</p></li>
+<li><p><strong>types</strong> (<em>List</em><em>[</em><em>Qtype</em><em>]</em>) – list of qtypes to inject</p></li>
+<li><p><strong>defs</strong> (<em>List</em><em>[</em><em>Qlassf</em><em>]</em>) – list of qlassf to inject</p></li>
+<li><p><strong>to_compile</strong> (<em>boolean</em><em>, </em><em>optional</em>) – if True, compile to quantum circuit (default: True)</p></li>
+<li><p><strong>compiler</strong> (<em>SupportedCompiler</em><em>, </em><em>optional</em>) – override default compiler (default: internal)</p></li>
+<li><p><strong>bool_optimizer</strong> (<em>BoolOptimizerProfile</em><em>, </em><em>optional</em>) – override default optimizer
+(default: bestWorkingOptimizer)</p></li>
+<li><p><strong>uncompute</strong> (<em>bool</em><em>, </em><em>optional</em>) – whenever uncompute input qubits during compilation
+(default: True)</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+</section>
+
+
+           </div>
+          </div>
+          <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
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+<li class="toctree-l2 current"><a class="current reference internal" href="#">qlasskit.qlassfun.qlassfa</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="#qlasskit.qlassfun.qlassfa"><code class="docutils literal notranslate"><span class="pre">qlassfa()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.qlassfun.QlassF.html">qlasskit.qlassfun.QlassF</a></li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.algorithms.qalgorithm.html">qlasskit.algorithms.qalgorithm</a></li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.algorithms.grover.Grover.html">qlasskit.algorithms.grover.Grover</a></li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.qcircuit.qcircuit.QCircuit.html">qlasskit.qcircuit.qcircuit.QCircuit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.html">qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper</a></li>
+<li class="toctree-l2"><a class="reference internal" href="qlasskit.qcircuit.gates.html">qlasskit.qcircuit.gates</a></li>
+</ul>
+</li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover_subset.html">Grover search: subset problem</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover_hash.html">Grover search: hash function preimage attack</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../example_grover_sudoku.html">Grover search: sudoku solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../example_unitary_of_f.html">Unitary of qlasskit function</a></li>
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+  <section id="qlasskit-qlassfun-qlassfa">
+<h1>qlasskit.qlassfun.qlassfa<a class="headerlink" href="#qlasskit-qlassfun-qlassfa" title="Link to this heading"></a></h1>
+<dl class="py function">
+<dt class="sig sig-object py" id="qlasskit.qlassfun.qlassfa">
+<span class="sig-prename descclassname"><span class="pre">qlasskit.qlassfun.</span></span><span class="sig-name descname"><span class="pre">qlassfa</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">types:</span> <span class="pre">~typing.List[~qlasskit.types.qtype.Qtype]</span> <span class="pre">=</span> <span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">defs:</span> <span class="pre">~typing.List[~qlasskit.qlassfun.QlassF]</span> <span class="pre">=</span> <span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">to_compile:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">compiler:</span> <span class="pre">~typing.Literal['internal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">'poc3'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">'tweedledum']</span> <span class="pre">=</span> <span class="pre">'internal'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bool_optimizer:</span> <span class="pre">~qlasskit.boolopt.bool_optimizer.BoolOptimizerProfile</span> <span class="pre">=</span> <span class="pre">&lt;qlasskit.boolopt.bool_optimizer.BoolOptimizerProfile</span> <span class="pre">object&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uncompute:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#qlasskit.qlassfun.qlassfa" title="Link to this definition"></a></dt>
+<dd><p>Decorator with parameters for qlassf</p>
+</dd></dl>
+
+</section>
+
+
+           </div>
+          </div>
+          <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
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+    <p>&#169; Copyright 2023, Davide Gessa (dakk).</p>
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\ No newline at end of file
diff --git a/genindex.html b/genindex.html
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+++ b/genindex.html
@@ -0,0 +1,199 @@
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+</ul>
+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_subset.html">Grover search: subset problem</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_hash.html">Grover search: hash function preimage attack</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_sudoku.html">Grover search: sudoku solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_unitary_of_f.html">Unitary of qlasskit function</a></li>
+</ul>
+
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+          <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
+           <div itemprop="articleBody">
+             
+
+<h1 id="index">Index</h1>
+
+<div class="genindex-jumpbox">
+ <a href="#_"><strong>_</strong></a>
+ | <a href="#G"><strong>G</strong></a>
+ | <a href="#M"><strong>M</strong></a>
+ | <a href="#Q"><strong>Q</strong></a>
+ 
+</div>
+<h2 id="_">_</h2>
+<table style="width: 100%" class="indextable genindextable"><tr>
+  <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="generated/qlasskit.algorithms.grover.Grover.html#qlasskit.algorithms.grover.Grover.__init__">__init__() (qlasskit.algorithms.grover.Grover method)</a>
+
+      <ul>
+        <li><a href="generated/qlasskit.qcircuit.qcircuit.QCircuit.html#qlasskit.qcircuit.qcircuit.QCircuit.__init__">(qlasskit.qcircuit.qcircuit.QCircuit method)</a>
+</li>
+        <li><a href="generated/qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.html#qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.__init__">(qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper method)</a>
+</li>
+        <li><a href="generated/qlasskit.qlassfun.QlassF.html#qlasskit.qlassfun.QlassF.__init__">(qlasskit.qlassfun.QlassF method)</a>
+</li>
+      </ul></li>
+  </ul></td>
+</tr></table>
+
+<h2 id="G">G</h2>
+<table style="width: 100%" class="indextable genindextable"><tr>
+  <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="generated/qlasskit.algorithms.grover.Grover.html#qlasskit.algorithms.grover.Grover">Grover (class in qlasskit.algorithms.grover)</a>
+</li>
+  </ul></td>
+</tr></table>
+
+<h2 id="M">M</h2>
+<table style="width: 100%" class="indextable genindextable"><tr>
+  <td style="width: 33%; vertical-align: top;"><ul>
+      <li>
+    module
+
+      <ul>
+        <li><a href="generated/qlasskit.algorithms.qalgorithm.html#module-qlasskit.algorithms.qalgorithm">qlasskit.algorithms.qalgorithm</a>
+</li>
+        <li><a href="generated/qlasskit.qcircuit.gates.html#module-qlasskit.qcircuit.gates">qlasskit.qcircuit.gates</a>
+</li>
+      </ul></li>
+  </ul></td>
+</tr></table>
+
+<h2 id="Q">Q</h2>
+<table style="width: 100%" class="indextable genindextable"><tr>
+  <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="generated/qlasskit.qcircuit.qcircuit.QCircuit.html#qlasskit.qcircuit.qcircuit.QCircuit">QCircuit (class in qlasskit.qcircuit.qcircuit)</a>
+</li>
+      <li><a href="generated/qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.html#qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper">QCircuitWrapper (class in qlasskit.qcircuit.qcircuitwrapper)</a>
+</li>
+      <li><a href="generated/qlasskit.qlassfun.QlassF.html#qlasskit.qlassfun.QlassF">QlassF (class in qlasskit.qlassfun)</a>
+</li>
+      <li><a href="generated/qlasskit.qlassfun.qlassf.html#qlasskit.qlassfun.qlassf">qlassf() (in module qlasskit.qlassfun)</a>
+</li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="generated/qlasskit.qlassfun.qlassfa.html#qlasskit.qlassfun.qlassfa">qlassfa() (in module qlasskit.qlassfun)</a>
+</li>
+      <li>
+    qlasskit.algorithms.qalgorithm
+
+      <ul>
+        <li><a href="generated/qlasskit.algorithms.qalgorithm.html#module-qlasskit.algorithms.qalgorithm">module</a>
+</li>
+      </ul></li>
+      <li>
+    qlasskit.qcircuit.gates
+
+      <ul>
+        <li><a href="generated/qlasskit.qcircuit.gates.html#module-qlasskit.qcircuit.gates">module</a>
+</li>
+      </ul></li>
+  </ul></td>
+</tr></table>
+
+
+
+           </div>
+          </div>
+          <footer>
+
+  <hr/>
+
+  <div role="contentinfo">
+    <p>&#169; Copyright 2023, Davide Gessa (dakk).</p>
+  </div>
+
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+    <a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
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\ No newline at end of file
diff --git a/how_it_works.html b/how_it_works.html
new file mode 100644
index 00000000..e17c57b5
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+++ b/how_it_works.html
@@ -0,0 +1,263 @@
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+<li class="toctree-l1"><a class="reference internal" href="quickstart.html">Quickstart</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">How it works</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="#ast-traslator">AST Traslator</a></li>
+<li class="toctree-l2"><a class="reference internal" href="#compiler">Compiler</a></li>
+<li class="toctree-l2"><a class="reference internal" href="#result">Result</a></li>
+</ul>
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+<li class="toctree-l1"><a class="reference internal" href="supported.html">Supported python subset</a></li>
+<li class="toctree-l1"><a class="reference internal" href="algorithms.html">Algorithms</a></li>
+<li class="toctree-l1"><a class="reference internal" href="api.html">API</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_subset.html">Grover search: subset problem</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_hash.html">Grover search: hash function preimage attack</a></li>
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+             
+  <section id="how-it-works">
+<h1>How it works<a class="headerlink" href="#how-it-works" title="Link to this heading"></a></h1>
+<p>To convert Python code into a quantum circuit, qlasskit implements a series of transformations:</p>
+<ol class="arabic simple">
+<li><p>It begins with the Python <em>AST</em> (Abstract Syntax Tree), converting it into a more streamlined form using the <code class="docutils literal notranslate"><span class="pre">ast2ast</span></code> module.</p></li>
+<li><p>Next, the streamlined AST is translated into <em>boolean expressions</em> as an intermediate step by the <code class="docutils literal notranslate"><span class="pre">ast2logic</span></code> module.
+During this phase, boolean expressions are refined and optimized in preparation for the final transformation.</p></li>
+<li><p>Finally, the <code class="docutils literal notranslate"><span class="pre">compiler</span></code> module takes these optimized boolean expressions and compiles them into a
+<em>quantum circuit</em>.</p></li>
+</ol>
+<p>Unlike other libraries that translate individual operations into quantum circuits before combining them,
+qlasskit constructs a singular boolean expression for each output qubit of the entire function.
+This unique approach facilitates advanced optimization leveraging boolean algebraic properties.</p>
+<p>For instance, let assume we have the following function:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qlasskit</span> <span class="kn">import</span> <span class="n">qlassf</span><span class="p">,</span> <span class="n">Qint2</span><span class="p">,</span> <span class="n">Qint4</span>
+<span class="kn">from</span> <span class="nn">qiskit</span> <span class="kn">import</span> <span class="n">QuantumCircuit</span>
+
+<span class="nd">@qlassf</span>
+<span class="k">def</span> <span class="nf">f_comp</span><span class="p">(</span><span class="n">b</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span> <span class="n">n</span><span class="p">:</span> <span class="n">Qint2</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Qint2</span><span class="p">:</span>
+      <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">3</span><span class="p">):</span>
+            <span class="n">n</span> <span class="o">+=</span> <span class="p">(</span><span class="mi">1</span> <span class="k">if</span> <span class="n">b</span> <span class="k">else</span> <span class="mi">2</span><span class="p">)</span>
+      <span class="k">return</span> <span class="n">n</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>If we decompose the algorithm in 3 separate additions and we compile them separately, we obtain the following circuit:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="nd">@qlassf</span>
+<span class="k">def</span> <span class="nf">f1</span><span class="p">(</span><span class="n">b</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span> <span class="n">n</span><span class="p">:</span> <span class="n">Qint2</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Qint2</span><span class="p">:</span>
+    <span class="k">return</span> <span class="n">n</span> <span class="o">+</span> <span class="p">(</span><span class="mi">1</span> <span class="k">if</span> <span class="n">b</span> <span class="k">else</span> <span class="mi">2</span><span class="p">)</span>
+
+<span class="n">qc</span> <span class="o">=</span> <span class="n">QuantumCircuit</span><span class="p">(</span><span class="n">f_comp</span><span class="o">.</span><span class="n">num_qubits</span> <span class="o">*</span> <span class="mi">2</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
+
+<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">3</span><span class="p">):</span>
+    <span class="n">qc</span><span class="o">.</span><span class="n">barrier</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;it_</span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="n">qc</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">f1</span><span class="o">.</span><span class="n">gate</span><span class="p">(),</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">i</span> <span class="o">*</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">5</span> <span class="o">+</span> <span class="n">i</span> <span class="o">*</span> <span class="mi">2</span><span class="p">)))</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Operations:&#39;</span><span class="p">,</span> <span class="n">qc</span><span class="o">.</span><span class="n">decompose</span><span class="p">()</span><span class="o">.</span><span class="n">count_ops</span><span class="p">())</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">decompose</span><span class="p">()</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="s2">&quot;mpl&quot;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Operations: OrderedDict([(&#39;cx&#39;, 12), (&#39;barrier&#39;, 3), (&#39;x&#39;, 3), (&#39;ccx&#39;, 3)])
+</pre></div>
+</div>
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/site-packages/qiskit/visualization/circuit/matplotlib.py:266: FutureWarning: The default matplotlib drawer scheme will be changed to &quot;iqp&quot; in a following release. To silence this warning, specify the current default explicitly as style=&quot;clifford&quot;, or the new default as style=&quot;iqp&quot;.
+  self._style, def_font_ratio = load_style(self._style)
+</pre></div>
+</div>
+<img alt="_images/99d44c6d50f9b254ae7c579012cd8627b241c498203712ce1fa7b4c31181df4d.png" src="_images/99d44c6d50f9b254ae7c579012cd8627b241c498203712ce1fa7b4c31181df4d.png" />
+</div>
+</div>
+<p>While if we compile the whole function to a quantum circuit using qlasskit, we obtain the following quantum circuit:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">qc</span> <span class="o">=</span> <span class="n">QuantumCircuit</span><span class="p">(</span><span class="n">f_comp</span><span class="o">.</span><span class="n">num_qubits</span><span class="p">)</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">f_comp</span><span class="o">.</span><span class="n">gate</span><span class="p">(),</span> <span class="n">f_comp</span><span class="o">.</span><span class="n">qubits</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Operations:&#39;</span><span class="p">,</span> <span class="n">qc</span><span class="o">.</span><span class="n">decompose</span><span class="p">()</span><span class="o">.</span><span class="n">count_ops</span><span class="p">())</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">decompose</span><span class="p">()</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="s2">&quot;mpl&quot;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Operations: OrderedDict([(&#39;cx&#39;, 4), (&#39;x&#39;, 1), (&#39;ccx&#39;, 1)])
+</pre></div>
+</div>
+<img alt="_images/bb602c4172678c017a5af45866c85d482b8102b2ff0882f9016d844672451041.png" src="_images/bb602c4172678c017a5af45866c85d482b8102b2ff0882f9016d844672451041.png" />
+</div>
+</div>
+<p>As we can see from the circuit drawings, qlasskit approach needs half the number of qubits and half the number of gates.</p>
+<section id="ast-traslator">
+<h2>AST Traslator<a class="headerlink" href="#ast-traslator" title="Link to this heading"></a></h2>
+<p>Given a python function, the <code class="docutils literal notranslate"><span class="pre">qlasskit.ast2logic</span></code> module walks its syntax tree translating all the statements /
+expressions to boolean expressions.</p>
+<p>For instance, the following function:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="nd">@qlassf</span>
+<span class="k">def</span> <span class="nf">f</span><span class="p">(</span><span class="n">n</span><span class="p">:</span> <span class="n">Qint4</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
+        <span class="k">return</span> <span class="n">n</span> <span class="o">==</span> <span class="mi">3</span>       
+</pre></div>
+</div>
+</div>
+</div>
+<p>Is translated to this boolean expression:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="n">expressions</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[(_ret, n.0 &amp; n.1 &amp; ~n.2 &amp; ~n.3)]
+</pre></div>
+</div>
+</div>
+</div>
+</section>
+<section id="compiler">
+<h2>Compiler<a class="headerlink" href="#compiler" title="Link to this heading"></a></h2>
+<p>The boolean expressions are then being fed to the `qlasskit.compiler`` which compiles boolean expressions
+to invertible circuits, introducing auxiliary qubits. In this step, the compiler will automatically uncompute
+auxiliary qubits in order to reduce the number of qubits needed and the circuit footprint.</p>
+<p>For the compilation, two backends are supported:</p>
+<ul class="simple">
+<li><p>InternalCompiler</p></li>
+<li><p>Tweedledum.xag_synth</p></li>
+</ul>
+</section>
+<section id="result">
+<h2>Result<a class="headerlink" href="#result" title="Link to this heading"></a></h2>
+<p>The result of the compiler is a quantum circuit represented with qlasskit <code class="docutils literal notranslate"><span class="pre">QCircuit</span></code>. This circuit
+can now be exported to one of the supported framework as a gate or as a standalone circuit.</p>
+<p>The previous example function <code class="docutils literal notranslate"><span class="pre">f</span></code>, is translated to the following quantum circuit: the
+result is available at qubit <code class="docutils literal notranslate"><span class="pre">q6</span></code>.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">f</span><span class="o">.</span><span class="n">export</span><span class="p">()</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="s1">&#39;mpl&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
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+             
+  <section id="qlasskit">
+<h1>Qlasskit<a class="headerlink" href="#qlasskit" title="Link to this heading"></a></h1>
+<p>Qlasskit is a Python library that allows quantum developers to write classical algorithms in pure
+Python and translate them into unitary operators (gates) for use in quantum circuits.</p>
+<div class="toctree-wrapper compound">
+<p class="caption" role="heading"><span class="caption-text">Qlasskit</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="quickstart.html">Quickstart</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="generated/qlasskit.algorithms.qalgorithm.html">qlasskit.algorithms.qalgorithm</a></li>
+<li class="toctree-l2"><a class="reference internal" href="generated/qlasskit.algorithms.grover.Grover.html">qlasskit.algorithms.grover.Grover</a></li>
+<li class="toctree-l2"><a class="reference internal" href="generated/qlasskit.qcircuit.qcircuit.QCircuit.html">qlasskit.qcircuit.qcircuit.QCircuit</a></li>
+<li class="toctree-l2"><a class="reference internal" href="generated/qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.html">qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper</a></li>
+<li class="toctree-l2"><a class="reference internal" href="generated/qlasskit.qcircuit.gates.html">qlasskit.qcircuit.gates</a></li>
+</ul>
+</li>
+</ul>
+</div>
+<div class="toctree-wrapper compound">
+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_subset.html">Grover search: subset problem</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_hash.html">Grover search: hash function preimage attack</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_sudoku.html">Grover search: sudoku solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_unitary_of_f.html">Unitary of qlasskit function</a></li>
+</ul>
+</div>
+</section>
+<section id="indices-and-tables">
+<h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Link to this heading"></a></h1>
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\ No newline at end of file
diff --git a/objects.inv b/objects.inv
new file mode 100644
index 00000000..d391a431
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diff --git a/py-modindex.html b/py-modindex.html
new file mode 100644
index 00000000..d16d126c
--- /dev/null
+++ b/py-modindex.html
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+<!DOCTYPE html>
+<html class="writer-html5" lang="en" data-content_root="./">
+<head>
+  <meta charset="utf-8" />
+  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
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+              <p class="caption" role="heading"><span class="caption-text">Qlasskit</span></p>
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+<li class="toctree-l1"><a class="reference internal" href="how_it_works.html">How it works</a></li>
+<li class="toctree-l1"><a class="reference internal" href="supported.html">Supported python subset</a></li>
+<li class="toctree-l1"><a class="reference internal" href="algorithms.html">Algorithms</a></li>
+<li class="toctree-l1"><a class="reference internal" href="api.html">API</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_subset.html">Grover search: subset problem</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_hash.html">Grover search: hash function preimage attack</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_sudoku.html">Grover search: sudoku solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_unitary_of_f.html">Unitary of qlasskit function</a></li>
+</ul>
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+
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+   <a href="#cap-q"><strong>q</strong></a>
+   </div>
+
+   <table class="indextable modindextable">
+     <tr class="pcap"><td></td><td>&#160;</td><td></td></tr>
+     <tr class="cap" id="cap-q"><td></td><td>
+       <strong>q</strong></td><td></td></tr>
+     <tr>
+       <td><img src="_static/minus.png" class="toggler"
+              id="toggle-1" style="display: none" alt="-" /></td>
+       <td>
+       <code class="xref">qlasskit</code></td><td>
+       <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="generated/qlasskit.algorithms.qalgorithm.html#module-qlasskit.algorithms.qalgorithm"><code class="xref">qlasskit.algorithms.qalgorithm</code></a></td><td>
+       <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="generated/qlasskit.qcircuit.gates.html#module-qlasskit.qcircuit.gates"><code class="xref">qlasskit.qcircuit.gates</code></a></td><td>
+       <em></em></td></tr>
+   </table>
+
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+           </div>
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+<!DOCTYPE html>
+<html class="writer-html5" lang="en" data-content_root="./">
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+              <p class="caption" role="heading"><span class="caption-text">Qlasskit</span></p>
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+<li class="toctree-l1 current"><a class="current reference internal" href="#">Quickstart</a></li>
+<li class="toctree-l1"><a class="reference internal" href="how_it_works.html">How it works</a></li>
+<li class="toctree-l1"><a class="reference internal" href="supported.html">Supported python subset</a></li>
+<li class="toctree-l1"><a class="reference internal" href="algorithms.html">Algorithms</a></li>
+<li class="toctree-l1"><a class="reference internal" href="api.html">API</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_subset.html">Grover search: subset problem</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_hash.html">Grover search: hash function preimage attack</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_sudoku.html">Grover search: sudoku solver</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_unitary_of_f.html">Unitary of qlasskit function</a></li>
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+             
+  <section id="quickstart">
+<h1>Quickstart<a class="headerlink" href="#quickstart" title="Link to this heading"></a></h1>
+<p>First install qlasskit using pip.</p>
+<p><code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">qlasskit</span></code></p>
+<p>We now define a qlassf function that sums two numbers:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qlasskit</span> <span class="kn">import</span> <span class="n">qlassf</span><span class="p">,</span> <span class="n">Qint2</span>
+
+<span class="nd">@qlassf</span> 
+<span class="k">def</span> <span class="nf">sum_two_numbers</span><span class="p">(</span><span class="n">a</span><span class="p">:</span> <span class="n">Qint2</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="n">Qint2</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Qint2</span><span class="p">:</span>
+    <span class="k">return</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span>
+</pre></div>
+</div>
+</div>
+</div>
+<p>We can now export the resulting quantum circuit to any supported framework:</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">circuit</span> <span class="o">=</span> <span class="n">sum_two_numbers</span><span class="o">.</span><span class="n">export</span><span class="p">(</span><span class="s1">&#39;qiskit&#39;</span><span class="p">)</span>
+<span class="n">circuit</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="s1">&#39;mpl&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/site-packages/qiskit/visualization/circuit/matplotlib.py:266: FutureWarning: The default matplotlib drawer scheme will be changed to &quot;iqp&quot; in a following release. To silence this warning, specify the current default explicitly as style=&quot;clifford&quot;, or the new default as style=&quot;iqp&quot;.
+  self._style, def_font_ratio = load_style(self._style)
+</pre></div>
+</div>
+<img alt="_images/27a749800d923fb69b5d38e7722422621f8acf4ee5c2b6f517f89d74a936444a.png" src="_images/27a749800d923fb69b5d38e7722422621f8acf4ee5c2b6f517f89d74a936444a.png" />
+</div>
+</div>
+<p>The qlassf function can be also exported as a gate, if the destination framwork supports it. We can use <code class="docutils literal notranslate"><span class="pre">encode_input</span></code> and <code class="docutils literal notranslate"><span class="pre">decode_output</span></code> in order to conver from/to high level types of qlasskit without worrying about the binary representation.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qiskit</span> <span class="kn">import</span> <span class="n">QuantumCircuit</span>
+
+<span class="n">qc</span> <span class="o">=</span> <span class="n">QuantumCircuit</span><span class="p">(</span><span class="n">sum_two_numbers</span><span class="o">.</span><span class="n">num_qubits</span><span class="p">,</span><span class="nb">len</span><span class="p">(</span><span class="n">sum_two_numbers</span><span class="o">.</span><span class="n">output_qubits</span><span class="p">))</span>
+
+<span class="n">qc</span><span class="o">.</span><span class="n">initialize</span><span class="p">(</span><span class="n">sum_two_numbers</span><span class="o">.</span><span class="n">encode_input</span><span class="p">(</span><span class="n">Qint2</span><span class="p">(</span><span class="mi">1</span><span class="p">),</span> <span class="n">Qint2</span><span class="p">(</span><span class="mi">2</span><span class="p">)),</span> <span class="n">sum_two_numbers</span><span class="o">.</span><span class="n">input_qubits</span><span class="p">)</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">sum_two_numbers</span><span class="o">.</span><span class="n">gate</span><span class="p">(</span><span class="s1">&#39;qiskit&#39;</span><span class="p">),</span> <span class="n">sum_two_numbers</span><span class="o">.</span><span class="n">qubits</span><span class="p">)</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">measure</span><span class="p">(</span><span class="n">sum_two_numbers</span><span class="o">.</span><span class="n">output_qubits</span><span class="p">,</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">sum_two_numbers</span><span class="o">.</span><span class="n">output_qubits</span><span class="p">)))</span>
+<span class="n">qc</span><span class="o">.</span><span class="n">draw</span><span class="p">(</span><span class="s1">&#39;mpl&#39;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<img alt="_images/c11daf869c135eac3524304f0b40bd3d1ae514f73d769f0de4a9d577f9da51ba.png" src="_images/c11daf869c135eac3524304f0b40bd3d1ae514f73d769f0de4a9d577f9da51ba.png" />
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qiskit</span> <span class="kn">import</span> <span class="n">Aer</span><span class="p">,</span> <span class="n">QuantumCircuit</span><span class="p">,</span> <span class="n">transpile</span>
+<span class="kn">from</span> <span class="nn">qiskit.visualization</span> <span class="kn">import</span> <span class="n">plot_histogram</span>
+
+<span class="n">simulator</span> <span class="o">=</span> <span class="n">Aer</span><span class="o">.</span><span class="n">get_backend</span><span class="p">(</span><span class="s2">&quot;aer_simulator&quot;</span><span class="p">)</span>
+<span class="n">circ</span> <span class="o">=</span> <span class="n">transpile</span><span class="p">(</span><span class="n">qc</span><span class="p">,</span> <span class="n">simulator</span><span class="p">)</span>
+<span class="n">result</span> <span class="o">=</span> <span class="n">simulator</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">circ</span><span class="p">)</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>
+<span class="n">counts</span> <span class="o">=</span> <span class="n">result</span><span class="o">.</span><span class="n">get_counts</span><span class="p">(</span><span class="n">circ</span><span class="p">)</span>
+
+<span class="n">counts_readable</span> <span class="o">=</span> <span class="n">sum_two_numbers</span><span class="o">.</span><span class="n">decode_counts</span><span class="p">(</span><span class="n">counts</span><span class="p">)</span>
+<span class="n">plot_histogram</span><span class="p">(</span><span class="n">counts_readable</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<img alt="_images/beafab15f915183b637909d537345580eba0f3a7fb66329311dd39909074d252.png" src="_images/beafab15f915183b637909d537345580eba0f3a7fb66329311dd39909074d252.png" />
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+<li class="toctree-l1"><a class="reference internal" href="example_grover_subset.html">Grover search: subset problem</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="example_unitary_of_f.html">Unitary of qlasskit function</a></li>
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diff --git a/searchindex.js b/searchindex.js
new file mode 100644
index 00000000..4f1a59ea
--- /dev/null
+++ b/searchindex.js
@@ -0,0 +1 @@
+Search.setIndex({"docnames": ["algorithms", "api", "example_grover", "example_grover_hash", "example_grover_subset", "example_grover_sudoku", "example_unitary_of_f", "generated/qlasskit.algorithms.grover.Grover", "generated/qlasskit.algorithms.qalgorithm", "generated/qlasskit.qcircuit.gates", "generated/qlasskit.qcircuit.qcircuit.QCircuit", "generated/qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper", "generated/qlasskit.qlassfun.QlassF", "generated/qlasskit.qlassfun.qlassf", "generated/qlasskit.qlassfun.qlassfa", "how_it_works", "index", "quickstart", "supported"], "filenames": ["algorithms.rst", "api.rst", "example_grover.ipynb", "example_grover_hash.ipynb", "example_grover_subset.ipynb", "example_grover_sudoku.ipynb", "example_unitary_of_f.ipynb", "generated/qlasskit.algorithms.grover.Grover.rst", "generated/qlasskit.algorithms.qalgorithm.rst", "generated/qlasskit.qcircuit.gates.rst", "generated/qlasskit.qcircuit.qcircuit.QCircuit.rst", 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"qlasskit-qcircuit-qcircuitwrapper-qcircuitwrapper"]], "qlasskit.qlassfun.QlassF": [[12, "qlasskit-qlassfun-qlassf"]], "qlasskit.qlassfun.qlassf": [[13, "qlasskit-qlassfun-qlassf"]], "qlasskit.qlassfun.qlassfa": [[14, "qlasskit-qlassfun-qlassfa"]], "How it works": [[15, "how-it-works"]], "AST Traslator": [[15, "ast-traslator"]], "Compiler": [[15, "compiler"]], "Result": [[15, "result"]], "Qlasskit": [[16, "qlasskit"], [16, null]], "Examples": [[16, null]], "Indices and tables": [[16, "indices-and-tables"]], "Quickstart": [[17, "quickstart"]], "Supported python subset": [[18, "supported-python-subset"]], "Types": [[18, "types"]], "bool": [[18, "bool"]], "Qint": [[18, "qint"]], "Tuple": [[18, "tuple"], [18, "id1"]], "List": [[18, "list"]], "Matrix": [[18, "matrix"]], "Expressions": [[18, "expressions"]], "Constants": [[18, "constants"]], "List (fixed size)": [[18, "list-fixed-size"]], "2D Matrix (fixed size)": [[18, "d-matrix-fixed-size"]], "Subscript": [[18, "subscript"]], "Boolean 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"qlasskit.qcircuit.qcircuit.QCircuit"]], "__init__() (qlasskit.qcircuit.qcircuit.qcircuit method)": [[10, "qlasskit.qcircuit.qcircuit.QCircuit.__init__"]], "qcircuitwrapper (class in qlasskit.qcircuit.qcircuitwrapper)": [[11, "qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper"]], "__init__() (qlasskit.qcircuit.qcircuitwrapper.qcircuitwrapper method)": [[11, "qlasskit.qcircuit.qcircuitwrapper.QCircuitWrapper.__init__"]], "qlassf (class in qlasskit.qlassfun)": [[12, "qlasskit.qlassfun.QlassF"]], "__init__() (qlasskit.qlassfun.qlassf method)": [[12, "qlasskit.qlassfun.QlassF.__init__"]], "qlassf() (in module qlasskit.qlassfun)": [[13, "qlasskit.qlassfun.qlassf"]], "qlassfa() (in module qlasskit.qlassfun)": [[14, "qlasskit.qlassfun.qlassfa"]]}})
\ No newline at end of file
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+++ b/supported.html
@@ -0,0 +1,353 @@
+<!DOCTYPE html>
+<html class="writer-html5" lang="en" data-content_root="./">
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+    <nav data-toggle="wy-nav-shift" class="wy-nav-side">
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+        <div class="wy-side-nav-search" >
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+          <a href="index.html" class="icon icon-home">
+            qlasskit
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+              <p class="caption" role="heading"><span class="caption-text">Qlasskit</span></p>
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+<li class="toctree-l1"><a class="reference internal" href="how_it_works.html">How it works</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Supported python subset</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="#types">Types</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="#bool">bool</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#qint">Qint</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#tuple">Tuple</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#list">List</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#matrix">Matrix</a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="#expressions">Expressions</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="#constants">Constants</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#id1">Tuple</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#list-fixed-size">List (fixed size)</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#d-matrix-fixed-size">2D Matrix (fixed size)</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#subscript">Subscript</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#boolean-operators">Boolean operators</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#if-expressions">If expressions</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#comparators">Comparators</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#unary-op">Unary Op</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#bin-op">Bin Op</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#function-call">Function call</a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="#statements">Statements</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="#assign">Assign</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#return">Return</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#for-loop">For loop</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#function-def">Function def</a></li>
+<li class="toctree-l3"><a class="reference internal" href="#if-then-else">If then else</a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="#quantum-hybrid">Quantum Hybrid</a></li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="algorithms.html">Algorithms</a></li>
+<li class="toctree-l1"><a class="reference internal" href="api.html">API</a></li>
+</ul>
+<p class="caption" role="heading"><span class="caption-text">Examples</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="example_grover.html">Grover search</a></li>
+<li class="toctree-l1"><a class="reference internal" href="example_grover_subset.html">Grover search: subset problem</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="example_unitary_of_f.html">Unitary of qlasskit function</a></li>
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+          <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
+           <div itemprop="articleBody">
+             
+  <section id="supported-python-subset">
+<h1>Supported python subset<a class="headerlink" href="#supported-python-subset" title="Link to this heading"></a></h1>
+<p>Qlasskit supports a subset of python. This subset will be expanded, but it is
+limited by the linearity of quantum circuits and by the number of qubits.</p>
+<p>The structure of a qlasskit function has the following pattern:</p>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@qlasskit</span>
+<span class="k">def</span> <span class="nf">f</span><span class="p">(</span><span class="n">param</span><span class="p">:</span> <span class="nb">type</span><span class="p">,</span> <span class="p">[</span><span class="o">...</span><span class="n">param</span><span class="p">:</span> <span class="nb">type</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="nb">type</span><span class="p">:</span>
+   <span class="n">statement</span>
+   <span class="o">...</span>
+   <span class="n">statement</span>
+</pre></div>
+</div>
+<section id="types">
+<h2>Types<a class="headerlink" href="#types" title="Link to this heading"></a></h2>
+<p>All types has a static size.</p>
+<section id="bool">
+<h3>bool<a class="headerlink" href="#bool" title="Link to this heading"></a></h3>
+<p>Boolean type.</p>
+</section>
+<section id="qint">
+<h3>Qint<a class="headerlink" href="#qint" title="Link to this heading"></a></h3>
+<p>Unsigned integers; this type has subtypes for different Qint sizes (Qint2, Qint4, Qint8, Qint12, Qint16).
+Single bit of the Qint are accessible by the subscript operator <cite>[]</cite>.</p>
+</section>
+<section id="tuple">
+<h3>Tuple<a class="headerlink" href="#tuple" title="Link to this heading"></a></h3>
+<p>Container type holding different types.</p>
+</section>
+<section id="list">
+<h3>List<a class="headerlink" href="#list" title="Link to this heading"></a></h3>
+<p>Qlist[T, size] denotes a fixed-size list in qlasskit.
+For example, the list <cite>[1,2,3]</cite> is typed as <cite>Qlist[Qint2,3]</cite>.</p>
+</section>
+<section id="matrix">
+<h3>Matrix<a class="headerlink" href="#matrix" title="Link to this heading"></a></h3>
+<p>Qmatrix[T, m, n] denotes a fixed-size list in qlasskit.
+For example, the matrix <cite>[[1,2],[3,4]]</cite> is typed as <cite>Qmatrix[Qint2,2,2]</cite>.</p>
+</section>
+</section>
+<section id="expressions">
+<h2>Expressions<a class="headerlink" href="#expressions" title="Link to this heading"></a></h2>
+<section id="constants">
+<h3>Constants<a class="headerlink" href="#constants" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kc">True</span>
+</pre></div>
+</div>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="mi">42</span>
+</pre></div>
+</div>
+</section>
+<section id="id1">
+<h3>Tuple<a class="headerlink" href="#id1" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>
+</pre></div>
+</div>
+</section>
+<section id="list-fixed-size">
+<h3>List (fixed size)<a class="headerlink" href="#list-fixed-size" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">]</span>
+</pre></div>
+</div>
+</section>
+<section id="d-matrix-fixed-size">
+<h3>2D Matrix (fixed size)<a class="headerlink" href="#d-matrix-fixed-size" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">],</span> <span class="p">[</span><span class="n">c</span><span class="p">,</span><span class="n">d</span><span class="p">]]</span>
+</pre></div>
+</div>
+</section>
+<section id="subscript">
+<h3>Subscript<a class="headerlink" href="#subscript" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">a</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
+</pre></div>
+</div>
+</section>
+<section id="boolean-operators">
+<h3>Boolean operators<a class="headerlink" href="#boolean-operators" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="ow">not</span> <span class="n">a</span>
+</pre></div>
+</div>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="ow">and</span> <span class="n">b</span>
+</pre></div>
+</div>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="ow">or</span> <span class="n">b</span>
+</pre></div>
+</div>
+</section>
+<section id="if-expressions">
+<h3>If expressions<a class="headerlink" href="#if-expressions" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="k">if</span> <span class="n">b</span> <span class="k">else</span> <span class="n">c</span>
+</pre></div>
+</div>
+</section>
+<section id="comparators">
+<h3>Comparators<a class="headerlink" href="#comparators" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="o">&gt;</span> <span class="n">b</span> <span class="ow">or</span> <span class="n">b</span> <span class="o">&lt;=</span> <span class="n">c</span> <span class="ow">and</span> <span class="n">c</span> <span class="o">==</span> <span class="n">d</span> <span class="ow">or</span> <span class="n">c</span> <span class="o">!=</span> <span class="n">a</span>
+</pre></div>
+</div>
+</section>
+<section id="unary-op">
+<h3>Unary Op<a class="headerlink" href="#unary-op" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="o">~</span><span class="n">a</span>
+</pre></div>
+</div>
+</section>
+<section id="bin-op">
+<h3>Bin Op<a class="headerlink" href="#bin-op" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="o">&lt;&lt;</span> <span class="mi">1</span>
+</pre></div>
+</div>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="o">&gt;&gt;</span> <span class="mi">2</span>
+</pre></div>
+</div>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="o">+</span> <span class="n">b</span>
+</pre></div>
+</div>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="o">-</span> <span class="n">b</span>
+</pre></div>
+</div>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="o">*</span> <span class="n">b</span>
+</pre></div>
+</div>
+</section>
+<section id="function-call">
+<h3>Function call<a class="headerlink" href="#function-call" title="Link to this heading"></a></h3>
+<p>Bultin functions:
+- <cite>print()</cite>: debug function, ignore by conversion
+- <cite>len(Tuple)</cite>, <cite>len(Qlist)`</cite>: returns the length of a tuple
+- <cite>max(a, b, …)</cite>, <cite>max(Tuple)</cite>, <cite>max(Qlist)</cite>: returns the max of a tuple
+- <cite>min(a, b, …)</cite>, <cite>min(Tuple)</cite>, <cite>min(Qlist)</cite>: returns the min of a tuple
+- <cite>sum(Tuple)</cite>, <cite>sum(Qlist)</cite>: returns the sum of the elemnts of a tuple / list
+- <cite>all(Tuple)</cite>, <cite>all(Qlist)</cite>: returns True if all of the elemnts are True
+- <cite>any(Tuple)</cite>, <cite>any(Qlist)</cite>: returns True if any of the elemnts are True</p>
+</section>
+</section>
+<section id="statements">
+<h2>Statements<a class="headerlink" href="#statements" title="Link to this heading"></a></h2>
+<section id="assign">
+<h3>Assign<a class="headerlink" href="#assign" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">c</span> <span class="o">=</span> <span class="ow">not</span> <span class="n">a</span>
+</pre></div>
+</div>
+</section>
+<section id="return">
+<h3>Return<a class="headerlink" href="#return" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">return</span> <span class="n">b</span><span class="o">+</span><span class="mi">1</span>
+</pre></div>
+</div>
+</section>
+<section id="for-loop">
+<h3>For loop<a class="headerlink" href="#for-loop" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">4</span><span class="p">):</span>
+   <span class="n">a</span> <span class="o">+=</span> <span class="n">i</span>
+</pre></div>
+</div>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>Please note that in qlasskit, for loops are unrolled during compilation. Therefore,
+it is essential that the number of iterations for each for loop is known at the
+time of compilation.</p>
+</div>
+</section>
+<section id="function-def">
+<h3>Function def<a class="headerlink" href="#function-def" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">f</span><span class="p">(</span><span class="n">t</span><span class="p">:</span> <span class="n">Qlist</span><span class="p">[</span><span class="n">Qint4</span><span class="p">,</span><span class="mi">2</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">Qint4</span><span class="p">:</span>
+   <span class="k">return</span> <span class="n">t</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">t</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
+</pre></div>
+</div>
+</section>
+<section id="if-then-else">
+<h3>If then else<a class="headerlink" href="#if-then-else" title="Link to this heading"></a></h3>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">c</span> <span class="o">=</span> <span class="mi">0</span>
+<span class="k">if</span> <span class="n">cond</span><span class="p">:</span>
+   <span class="n">c</span> <span class="o">+=</span> <span class="mi">12</span>
+<span class="k">else</span><span class="p">:</span>
+   <span class="n">c</span> <span class="o">+=</span> <span class="mi">13</span>
+</pre></div>
+</div>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>At present, the if-then-else statement in qlasskit is designed to support branch bodies
+that exclusively contain assignment statements.</p>
+</div>
+</section>
+</section>
+<section id="quantum-hybrid">
+<h2>Quantum Hybrid<a class="headerlink" href="#quantum-hybrid" title="Link to this heading"></a></h2>
+<p>In a qlassf function, you have the option to utilize quantum gates through the Q module. It’s
+important to keep in mind that incorporating quantum gates within a qlasskit function leads
+to a Python function that exhibits distinct behaviors compared to its quantum counterpart.</p>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">bell</span><span class="p">(</span><span class="n">a</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="nb">bool</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
+   <span class="k">return</span> <span class="n">Q</span><span class="o">.</span><span class="n">CX</span><span class="p">(</span><span class="n">Q</span><span class="o">.</span><span class="n">H</span><span class="p">(</span><span class="n">a</span><span class="p">),</span> <span class="n">b</span><span class="p">)</span>
+</pre></div>
+</div>
+</section>
+</section>
+
+
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