Small doc changes in tomo. (#143)

CHANGELOG.md

@@ -7,6 +7,9 @@ Improvements and Changes:
 
 - Fixed the years in this Change log file 2018 -> 2019
 - Added linear inversion process tomography (gh-142)
+- Changed qubit tensor factor ordering of state tomography estimates to match that of process tomography, e.g. 
+tomographizing the plus eigenstate of `X0 * Z1` and passing in `qubits = [0,1]` will yield the state 
+estimate corresponding to `|+0> = (1, 0, 1, 0)/sqrt(2)` rather than `|0+>` (gh-142)
 
 
 v0.6 (June 11, 2019)

forest/benchmarking/tomography.py

@@ -488,7 +488,7 @@ def linear_inv_process_estimate(results: List[ExperimentResult], qubits: List[in
 
     This is the simplest process tomography post processing. To use this function,
     collect process tomography data with :py:func:`generate_process_tomography_experiment`
-    and :py:func:`~pyquil.operator_estimation.measure_observables`.
+    and :py:func:`~forest.benchmarking.observable_estimation.estimate_observables`.
 
     For more details on this post-processing technique,
     see https://en.wikipedia.org/wiki/Quantum_tomography#Linear_inversion or
@@ -503,7 +503,7 @@ def linear_inv_process_estimate(results: List[ExperimentResult], qubits: List[in
     :param qubits: All qubits that were tomographized. This specifies the order in
         which qubits will be kron'ed together; the first qubit in the list is the left-most
         tensor factor.
-    :return: A point estimate of the quantum state rho.
+    :return: A point estimate of the quantum process represented by a Choi matrix
     """
     # state2matrix and pauli2matrix use pyquil tensor factor ordering where the least significant
     # qubit, e.g. qubit 0, is the right-most tensor factor. We stick with the standard convention