Prepare 0.17.0 release (Qiskit/qiskit#6075)

* Prepare 0.17.0 release

To prepare for the upcoming 0.17.0 release this commit moves all the
release notes into a 0.17 subdirectory to keep them separate from future
development notes post-release. It also adds an incomplete release note
to add the prelude section providing the high level overview of the
release. When this merges it should be the commit used to tag the 0.17.0
release.

* Add feature note for aqua migrated modules

* Update release notes abd add piecewise chebyshev to docs and library export

* Update more release notes and add abstract pass classes to docs

* More release note updates

* Update more release notes and add clifford_decompose to api docs

* Add RZXCalibration pass and templates to docs and update release notes

* Update more release notes

* Fix typo in decompose_clifford imports and release notes

* Fix docs build

* Add hellinger_distance to docs

* Add RZXCalibrationBuilder to the docs

* More release note updates

* Fix import error

* Fix RZXCalibrationBuilder docstring

* Finish updating the new feature release notes

* Fix lint

* Apply suggestions from code review

Co-authored-by: Julien Gacon <gaconju@gmail.com>

* Move new release notes to 0.17 dir and update

* Fix RVGate docs and start updating upgrade notes

* Fix PauliGate example circuit visualization

* Fix typo

* More release note updates

* Update meas_map release note again

* Fix whitespace in meas_map release note

* Fix docs build

* Update almost all of the upgrade notes

* Add latex to docs job env

* Revert "Add latex to docs job env"

This reverts commit 8080cb58ea0c0faad270197c61d2cececff8da1e.

* Remove latex drawing from the release notes

Getting the texlive distribution with qcircuit installed in CI is
proving problematic in the interest of time and finishing the other
releasenotes instead of relying on it this just changes the latex drawer
jupyter execute to be a code block and not depend on being able to run
pdftlatex at docs build time.

* Remove fix note for unreleased feature

* Move and update new release notes

* Remove unnecessary upgrade note about internal API changes

* More release note updates

* More release note updates

* Even more release note updates

* Fix syntax error

* Fix docs build

* Move new release notes and fix docs issues from Qiskit/qiskit#5609

* Update more release notes

* Move new release notes

* More release note updates

* Finish fixes notes

* Fix docs build

* Update more relaese notes

* Apply suggestions from code review

Co-authored-by: Naoki Kanazawa <nkanazawa1989@gmail.com>

* More note fixes

* Update new release notes

* Apply suggestions from code review

Co-authored-by: Kevin Krsulich <kevin@krsulich.net>

* Move and update new release notes

* Apply suggestions from code review

Co-authored-by: Kevin Krsulich <kevin@krsulich.net>

* cleaning up docs for vqe

* clean up extend

* Fix reno merge commit error

* Revert accidental tox.ini change

* Tweak release note wording

* Move and update new release notes

* Attempt to retrigger azure

Co-authored-by: Julien Gacon <gaconju@gmail.com>
Co-authored-by: Lauren Capelluto <laurencapelluto@gmail.com>
Co-authored-by: Naoki Kanazawa <nkanazawa1989@gmail.com>
Co-authored-by: Kevin Krsulich <kevin@krsulich.net>
Co-authored-by: Jay Gambetta <jay.gambetta@us.ibm.com>

qiskit_algorithms/minimum_eigen_solvers/qaoa.py

@@ -33,8 +33,8 @@ class QAOA(VQE):
 
     `QAOA <https://arxiv.org/abs/1411.4028>`__ is a well-known algorithm for finding approximate
     solutions to combinatorial-optimization problems.
-    The QAOA implementation directly extends :class:`VQE` and inherits VQE's
-    general hybrid optimization structure.
+
+    The QAOA implementation directly extends :class:`VQE` and inherits VQE's optimization structure.
     However, unlike VQE, which can be configured with arbitrary ansatzes,
     QAOA uses its own fine-tuned ansatz, which comprises :math:`p` parameterized global
     :math:`x` rotations and :math:`p` different parameterizations of the problem hamiltonian.

qiskit_algorithms/minimum_eigen_solvers/vqe.py

@@ -45,8 +45,8 @@
 class VQE(VariationalAlgorithm, MinimumEigensolver):
     r"""The Variational Quantum Eigensolver algorithm.
 
-    `VQE <https://arxiv.org/abs/1304.3061>`__ is a hybrid algorithm that uses a
-    variational technique and interleaves quantum and classical computations in order to find
+    `VQE <https://arxiv.org/abs/1304.3061>`__ is a quantum algorithm that uses a
+    variational technique to find
     the minimum eigenvalue of the Hamiltonian :math:`H` of a given system.
 
     An instance of VQE requires defining two algorithmic sub-components: