Deploying to gh-pages from @ 13a57e1 🚀

.buildinfo

@@ -1,4 +1,4 @@
 # 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: dc082803aafb67b44c4b36686e4cbb52
+config: e83baf37b7a96495b000511a4b9196fc
 tags: 645f666f9bcd5a90fca523b33c5a78b7

_sources/index.rst.txt

@@ -20,7 +20,7 @@ The code comprises various modules revolving around:
 - translating from the second-quantized to the qubit space
 - a quantum circuit library of natural science targeted ansatze
 - natural science specific algorithms and utilities to make the use of
-  algorithms from `Qiskit Algorithms <https://qiskit.org/ecosystem/algorithms/>`_ easier
+  algorithms from `Qiskit Algorithms <https://qiskit-community.github.io/qiskit-algorithms/>`_ easier
 - and much more
 
 

_sources/tutorials/03_ground_state_solvers.ipynb.txt

@@ -127,7 +127,7 @@
     "\n",
     "1. An Estimator primitive: these were released as part of Qiskit Terra 0.22. To learn more about primitives, check out [this resource](https://qiskit.org/documentation/apidoc/primitives.html).\n",
     "2. A variational form: here we use the Unitary Coupled Cluster (UCC) ansatz (see for instance [Physical Review A 98.2 (2018): 022322]). Since it is a chemistry standard, a factory is already available allowing a fast initialization of a VQE with UCC. The default is to use all single and double excitations. However, the excitation type (S, D, SD) as well as other parameters can be selected. We also prepend the `UCCSD` variational form with a `HartreeFock` initial state, which initializes the occupation of our qubits according to the problem which we are trying solve.\n",
-    "3. An optimizer: this is the classical piece of code in charge of optimizing the parameters in our variational form. See [the corresponding documentation](https://qiskit.org/ecosystem/algorithms/apidocs/qiskit_algorithms.optimizers.html) for more information.\n",
+    "3. An optimizer: this is the classical piece of code in charge of optimizing the parameters in our variational form. See [the corresponding documentation](https://qiskit-community.github.io/qiskit-algorithms/apidocs/qiskit_algorithms.optimizers.html) for more information.\n",
     "\n",
     "One could also use any available ansatz / initial state or even define one's own. For instance,"
    ]

apidocs/qiskit_nature.second_q.algorithms.html

@@ -663,7 +663,7 @@ <h2>Ground State Solvers<a class="headerlink" href="#ground-state-solvers" title
 </section>
 <section id="initial-points">
 <h2>Initial Points<a class="headerlink" href="#initial-points" title="Permalink to this heading">#</a></h2>
-<p>When using variational algorithms such as the <a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.VQE.html#qiskit_algorithms.VQE" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">VQE</span></code></a>
+<p>When using variational algorithms such as the <a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.VQE.html#qiskit_algorithms.VQE" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">VQE</span></code></a>
 it may be necessary to set the initial parameters for the optimizer to a specific value (by default,
 the optimizer will start from a random point). This depends on the problem one is trying to solve as
 well as the ansatz used to solve the problem. To this extent, the following submodule provides

getting_started.html

@@ -685,7 +685,7 @@ <h2>Installing Qiskit Nature from Source</h2><p>Using the same development envir
 <section id="ready-to-get-going">
 <h2>Ready to get going?…<a class="headerlink" href="#ready-to-get-going" title="Permalink to this heading">#</a></h2>
 <p>Now that Qiskit Nature is installed, let’s try a chemistry application experiment
-using the <a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.VQE.html#qiskit_algorithms.VQE" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">VQE</span></code></a> (Variational
+using the <a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.VQE.html#qiskit_algorithms.VQE" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">VQE</span></code></a> (Variational
 Quantum Eigensolver) algorithm to compute the ground-state (minimum) energy of a
 molecule.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qiskit_nature.units</span> <span class="kn">import</span> <span class="n">DistanceUnit</span>
@@ -783,19 +783,19 @@ <h2>Ready to get going?…<a class="headerlink" href="#ready-to-get-going" title
 are provided to it; a reduction in complexity that is particularly advantageous
 for NISQ computers.</p>
 <p>For actually finding the ground state solution, the Variational Quantum
-Eigensolver (<a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.VQE.html#qiskit_algorithms.VQE" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">VQE</span></code></a>) algorithm is
+Eigensolver (<a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.VQE.html#qiskit_algorithms.VQE" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">VQE</span></code></a>) algorithm is
 used. Its main three components are the estimator primitive
-(<a class="reference external" href="https://qiskit.org/documentation/stubs/qiskit.primitives.Estimator.html#qiskit.primitives.Estimator" title="(in Qiskit v0.45)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Estimator</span></code></a>), wavefunction ansatz
+(<a class="reference external" href="https://docs.quantum.ibm.com/api/qiskit/qiskit.primitives.Estimator" title="(in Qiskit v0.45)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Estimator</span></code></a>), wavefunction ansatz
 (<a class="reference internal" href="stubs/qiskit_nature.second_q.circuit.library.UCCSD.html#qiskit_nature.second_q.circuit.library.UCCSD" title="qiskit_nature.second_q.circuit.library.UCCSD"><code class="xref py py-class docutils literal notranslate"><span class="pre">UCCSD</span></code></a>), and optimizer
-(<a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.optimizers.L_BFGS_B.html#qiskit_algorithms.optimizers.L_BFGS_B" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">L_BFGS_B</span></code></a>).
+(<a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.optimizers.L_BFGS_B.html#qiskit_algorithms.optimizers.L_BFGS_B" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">L_BFGS_B</span></code></a>).
 The <a class="reference internal" href="stubs/qiskit_nature.second_q.circuit.library.UCCSD.html#qiskit_nature.second_q.circuit.library.UCCSD" title="qiskit_nature.second_q.circuit.library.UCCSD"><code class="xref py py-class docutils literal notranslate"><span class="pre">UCCSD</span></code></a> component is the only
 one provided directly by Qiskit Nature and it is usually paired with the
 <a class="reference internal" href="stubs/qiskit_nature.second_q.circuit.library.HartreeFock.html#qiskit_nature.second_q.circuit.library.HartreeFock" title="qiskit_nature.second_q.circuit.library.HartreeFock"><code class="xref py py-class docutils literal notranslate"><span class="pre">HartreeFock</span></code></a> initial state and
 an all-zero initial point for the optimizer.</p>
 <p>The entire problem is then solved using a
 <a class="reference internal" href="stubs/qiskit_nature.second_q.algorithms.GroundStateEigensolver.html#qiskit_nature.second_q.algorithms.GroundStateEigensolver" title="qiskit_nature.second_q.algorithms.GroundStateEigensolver"><code class="xref py py-class docutils literal notranslate"><span class="pre">GroundStateEigensolver</span></code></a> which wraps
 both, the <a class="reference internal" href="stubs/qiskit_nature.second_q.mappers.ParityMapper.html#qiskit_nature.second_q.mappers.ParityMapper" title="qiskit_nature.second_q.mappers.ParityMapper"><code class="xref py py-class docutils literal notranslate"><span class="pre">ParityMapper</span></code></a> and
-<a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.VQE.html#qiskit_algorithms.VQE" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">VQE</span></code></a>. Since an
+<a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.VQE.html#qiskit_algorithms.VQE" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">VQE</span></code></a>. Since an
 <a class="reference internal" href="stubs/qiskit_nature.second_q.problems.ElectronicStructureProblem.html#qiskit_nature.second_q.problems.ElectronicStructureProblem" title="qiskit_nature.second_q.problems.ElectronicStructureProblem"><code class="xref py py-class docutils literal notranslate"><span class="pre">ElectronicStructureProblem</span></code></a> is provided
 to it (which was the output of the
 <a class="reference internal" href="stubs/qiskit_nature.second_q.drivers.PySCFDriver.html#qiskit_nature.second_q.drivers.PySCFDriver" title="qiskit_nature.second_q.drivers.PySCFDriver"><code class="xref py py-class docutils literal notranslate"><span class="pre">PySCFDriver</span></code></a>) it also returns an

howtos/adapt_vqe.html

@@ -588,7 +588,7 @@
         <article role="main">
           <br><br><br><section id="find-ground-state-energy-using-adaptvqe">
 <h1>Find ground state energy using AdaptVQE<a class="headerlink" href="#find-ground-state-energy-using-adaptvqe" title="Permalink to this heading">#</a></h1>
-<p>This guide outlines how the <a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.AdaptVQE.html#qiskit_algorithms.AdaptVQE" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">AdaptVQE</span></code></a> algorithm can
+<p>This guide outlines how the <a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.AdaptVQE.html#qiskit_algorithms.AdaptVQE" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">AdaptVQE</span></code></a> algorithm can
 be used to find the ground state solutions of natural science problems.</p>
 <ol class="arabic simple">
 <li><p>We obtain an <a class="reference internal" href="../stubs/qiskit_nature.second_q.problems.ElectronicStructureProblem.html#qiskit_nature.second_q.problems.ElectronicStructureProblem" title="qiskit_nature.second_q.problems.ElectronicStructureProblem"><code class="xref py py-class docutils literal notranslate"><span class="pre">ElectronicStructureProblem</span></code></a>
@@ -623,7 +623,7 @@ <h1>Find ground state energy using AdaptVQE<a class="headerlink" href="#find-gro
 </pre></div>
 </div>
 <ol class="arabic simple" start="4">
-<li><p>We setup a <a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.VQE.html#qiskit_algorithms.VQE" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">VQE</span></code></a>:</p></li>
+<li><p>We setup a <a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.VQE.html#qiskit_algorithms.VQE" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">VQE</span></code></a>:</p></li>
 </ol>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
 <span class="kn">from</span> <span class="nn">qiskit_algorithms</span> <span class="kn">import</span> <span class="n">VQE</span>
@@ -634,7 +634,7 @@ <h1>Find ground state energy using AdaptVQE<a class="headerlink" href="#find-gro
 </pre></div>
 </div>
 <ol class="arabic simple" start="5">
-<li><p>We setup the <a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.AdaptVQE.html#qiskit_algorithms.AdaptVQE" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">AdaptVQE</span></code></a>:</p></li>
+<li><p>We setup the <a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.AdaptVQE.html#qiskit_algorithms.AdaptVQE" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">AdaptVQE</span></code></a>:</p></li>
 </ol>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qiskit_algorithms</span> <span class="kn">import</span> <span class="n">AdaptVQE</span>
 <span class="n">adapt_vqe</span> <span class="o">=</span> <span class="n">AdaptVQE</span><span class="p">(</span><span class="n">vqe</span><span class="p">)</span>

howtos/numpy_eigensolver.html

@@ -589,8 +589,8 @@
           <br><br><br><section id="find-excited-state-energies-using-the-numpyeigensolver">
 <span id="how-to-numpy"></span><h1>Find excited state energies using the NumPyEigensolver<a class="headerlink" href="#find-excited-state-energies-using-the-numpyeigensolver" title="Permalink to this heading">#</a></h1>
 <p>In order to ensure a physically meaningful excited states of a hamiltonian are found when using the
-<a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.NumPyEigensolver.html#qiskit_algorithms.NumPyEigensolver" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">NumPyEigensolver</span></code></a> one needs to set the
-<a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.NumPyEigensolver.html#qiskit_algorithms.NumPyEigensolver.filter_criterion" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-attr docutils literal notranslate"><span class="pre">filter_criterion</span></code></a> attribute
+<a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.NumPyEigensolver.html#qiskit_algorithms.NumPyEigensolver" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">NumPyEigensolver</span></code></a> one needs to set the
+<a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.NumPyEigensolver.html#qiskit_algorithms.NumPyEigensolver.filter_criterion" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-attr docutils literal notranslate"><span class="pre">filter_criterion</span></code></a> attribute
 of the solver.</p>
 <p>Subclasses of <a class="reference internal" href="../stubs/qiskit_nature.second_q.problems.BaseProblem.html#qiskit_nature.second_q.problems.BaseProblem" title="qiskit_nature.second_q.problems.BaseProblem"><code class="xref py py-class docutils literal notranslate"><span class="pre">BaseProblem</span></code></a> in Qiskit Nature provide the
 <a class="reference internal" href="../stubs/qiskit_nature.second_q.problems.BaseProblem.html#qiskit_nature.second_q.problems.BaseProblem.get_default_filter_criterion" title="qiskit_nature.second_q.problems.BaseProblem.get_default_filter_criterion"><code class="xref py py-meth docutils literal notranslate"><span class="pre">get_default_filter_criterion()</span></code></a> method which
@@ -613,7 +613,7 @@
 </pre></div>
 </div>
 <ol class="arabic simple" start="3">
-<li><p>We setup our <a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.NumPyEigensolver.html#qiskit_algorithms.NumPyEigensolver" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">NumPyEigensolver</span></code></a>:</p></li>
+<li><p>We setup our <a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.NumPyEigensolver.html#qiskit_algorithms.NumPyEigensolver" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">NumPyEigensolver</span></code></a>:</p></li>
 </ol>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">qiskit_algorithms</span> <span class="kn">import</span> <span class="n">NumPyEigensolver</span>
 <span class="n">algo</span> <span class="o">=</span> <span class="n">NumPyEigensolver</span><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>

howtos/numpy_minimum_eigensolver.html

@@ -589,8 +589,8 @@
           <br><br><br><section id="find-ground-state-energy-using-the-numpyminimumeigensolver">
 <span id="how-to-numpy-min"></span><h1>Find ground state energy using the NumPyMinimumEigensolver<a class="headerlink" href="#find-ground-state-energy-using-the-numpyminimumeigensolver" title="Permalink to this heading">#</a></h1>
 <p>In order to ensure a physically meaningful ground state of a hamiltonian is found when using the
-<a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.NumPyMinimumEigensolver.html#qiskit_algorithms.NumPyMinimumEigensolver" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">NumPyMinimumEigensolver</span></code></a> one needs to set the
-<a class="reference external" href="https://qiskit.org/ecosystem/algorithms/stubs/qiskit_algorithms.NumPyMinimumEigensolver.html#qiskit_algorithms.NumPyMinimumEigensolver.filter_criterion" title="(in Qiskit Algorithms v0.2.1)"><code class="xref py py-attr docutils literal notranslate"><span class="pre">filter_criterion</span></code></a> attribute
+<a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.NumPyMinimumEigensolver.html#qiskit_algorithms.NumPyMinimumEigensolver" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-class docutils literal notranslate"><span class="pre">NumPyMinimumEigensolver</span></code></a> one needs to set the
+<a class="reference external" href="https://qiskit-community.github.io/qiskit-algorithms/stubs/qiskit_algorithms.NumPyMinimumEigensolver.html#qiskit_algorithms.NumPyMinimumEigensolver.filter_criterion" title="(in Qiskit Algorithms v0.2.2)"><code class="xref py py-attr docutils literal notranslate"><span class="pre">filter_criterion</span></code></a> attribute
 of the solver.</p>
 <p>Subclasses of <a class="reference internal" href="../stubs/qiskit_nature.second_q.problems.BaseProblem.html#qiskit_nature.second_q.problems.BaseProblem" title="qiskit_nature.second_q.problems.BaseProblem"><code class="xref py py-class docutils literal notranslate"><span class="pre">BaseProblem</span></code></a> in Qiskit Nature provide the
 <a class="reference internal" href="../stubs/qiskit_nature.second_q.problems.BaseProblem.html#qiskit_nature.second_q.problems.BaseProblem.get_default_filter_criterion" title="qiskit_nature.second_q.problems.BaseProblem.get_default_filter_criterion"><code class="xref py py-meth docutils literal notranslate"><span class="pre">get_default_filter_criterion()</span></code></a> method which