Merge branch 'main' into feature/stark_p1_frequency_scan

.github/workflows/cron-staging.yml

@@ -10,7 +10,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [3.8, 3.9, "3.10", "3.11"]
+        python-version: [3.8, "3.11"]
         os: ["ubuntu-latest", "macOS-latest", "windows-latest"]
     steps:
       - name: Print Concurrency Group

.github/workflows/main.yml

@@ -15,7 +15,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [3.8, 3.9, "3.10", "3.11"]
+        python-version: [3.8, "3.11"]
         os: ["ubuntu-latest", "macOS-latest", "windows-latest"]
     steps:
       - name: Print Concurrency Group
@@ -39,25 +39,20 @@ jobs:
             ${{ runner.os }}-${{ matrix.python-version }}-pip-tests-
             ${{ runner.os }}-${{ matrix.python-version }}-pip-
             ${{ runner.os }}-${{ matrix.python-version }}
+      - name: Stestr cache
+        uses: actions/cache@v3
+        with:
+          path: .stestr
+          key: stestr-${{ runner.os }}-${{ matrix.python-version }}
+          restore-keys: |
+            stestr-${{ runner.os }}-
+            stestr-
       - name: Install Deps
-        run: python -m pip install -U "tox==3.27.1" setuptools virtualenv wheel
-      - name: Install and Run Tests (Windows and Linux)
+        run: python -m pip install -U tox setuptools virtualenv wheel stestr
+      - name: Install and Run Tests
         run: tox -e py
-        if: runner.os != 'macOS'
-      - name: Install and Run Tests (Macs only)
-        run: tox -e cover
-        if: runner.os == 'macOS'
-        env:
-          OMP_NUM_THREADS: 1
-      - name: Report coverage to coveralls.io (Macs only)
-        if: runner.os == 'macOS'
-        uses: coverallsapp/github-action@v2
-        env:
-          ACTIONS_RUNNER_DEBUG: 1
-        with:
-          github-token: ${{ secrets.GITHUB_TOKEN }}
-          flag-name: unit-tests_python${{ matrix.python-version }}-${{ matrix.os }}
-          path-to-lcov: coverage.lcov
+      - name: Clean up stestr cache
+        run: stestr history remove all
 
   lint:
     name: lint
@@ -98,7 +93,7 @@ jobs:
           python -m pip install -U tox
           sudo apt-get install -y pandoc graphviz
       - name: Build Docs
-        run: tox -edocs
+        run: tox -edocs-parallel
       - name: Compress Artifacts
         run: |
           mkdir artifacts

.github/workflows/release.yml

@@ -7,14 +7,17 @@ jobs:
   wheel-build:
     name: Build and Publish Release Artifacts
     runs-on: ubuntu-latest
+    environment: release
+    permissions:
+      id-token: write
     steps:
       - uses: actions/checkout@v3
       - uses: actions/setup-python@v4
         name: Install Python
         with:
           python-version: '3.8'
       - name: Install Deps
-        run: pip install -U twine wheel
+        run: pip install -U wheel
       - name: Build Artifacts
         run: |
           python setup.py sdist
@@ -24,7 +27,4 @@ jobs:
         with:
           path: ./dist/qiskit*
       - name: Publish to PyPi
-        env:
-          TWINE_PASSWORD: ${{ secrets.TWINE_PASSWORD }}
-          TWINE_USERNAME: qiskit
-        run: twine upload dist/qiskit*
+        uses: pypa/gh-action-pypi-publish@release/v1

.stestr.conf

@@ -1,2 +1,3 @@
 [DEFAULT]
 test_path=./test
+parallel_class=True

CODE_OF_CONDUCT.md

@@ -1,7 +1,7 @@
 <!-- Copyright Contributors to the Qiskit project. -->
 
 # Code of Conduct
-All members of this project agree to adhere to the Qiskit Code of Conduct listed at [https://github.com/Qiskit/qiskit-metapackage/blob/master/CODE_OF_CONDUCT.md](https://github.com/Qiskit/qiskit-metapackage/blob/master/CODE_OF_CONDUCT.md)
+All members of this project agree to adhere to the [Qiskit Code of Conduct](https://github.com/Qiskit/qiskit/blob/main/CODE_OF_CONDUCT.md).
 
 ----
 

CONTRIBUTING.md

@@ -121,6 +121,8 @@ To run a method:
 tox -- -n test.python.test_examples.TestPythonExamples.test_all_examples
 ```
 
+Note that tests will fail automatically if they do not finish execution within 60 seconds.
+
 #### STDOUT/STDERR and logging capture
 
 When running tests in parallel using `stestr` either via tox, the Makefile (`make

README.md

@@ -3,7 +3,6 @@
 [![License](https://img.shields.io/github/license/Qiskit-Extensions/qiskit-experiments.svg)](https://opensource.org/licenses/Apache-2.0)
 [![Release](https://img.shields.io/github/release/Qiskit-Extensions/qiskit-experiments.svg)](https://github.com/Qiskit-Extensions/qiskit-experiments/releases)
 ![Python](https://img.shields.io/pypi/pyversions/qiskit-experiments.svg)
-[![Coverage Status](https://coveralls.io/repos/github/Qiskit-Extensions/qiskit-experiments/badge.svg?branch=main)](https://coveralls.io/github/Qiskit-Extensions/qiskit-experiments?branch=main)
 [![DOI](https://joss.theoj.org/papers/10.21105/joss.05329/status.svg)](https://doi.org/10.21105/joss.05329)
 
 **Qiskit Experiments** is a repository that builds tools for building, running,

docs/conf.py

@@ -53,7 +53,6 @@
     "sphinx.ext.autodoc",
     "sphinx.ext.autosummary",
     "sphinx.ext.mathjax",
-    "sphinx.ext.viewcode",
     "sphinx.ext.extlinks",
     "sphinx_copybutton",
     "jupyter_sphinx",
@@ -69,11 +68,14 @@
     "sphinx_remove_toctrees",
 ]
 
-# Remove stubs from the toctree by default because the full build is slow
-# This is turned off for docs deployment
-if not os.getenv("FULL_TOCTREE", None):
+if os.getenv("PROD_BUILD", None):
+    # Turn on view code source for production build
+    extensions.append("sphinx.ext.viewcode")
+else:
+    # Remove stubs from the toctree for non-prod build because the full build is slow
     remove_from_toctrees = ["stubs/*"]
 
+
 html_static_path = ["_static"]
 templates_path = ["_templates"]
 # Manually add the gallery CSS file for now

docs/howtos/figure_generation.rst

@@ -0,0 +1,45 @@
+Control figure generation 
+=========================
+
+Problem
+-------
+
+You want to change the default behavior where figures are generated with every experiment.
+
+Solution
+--------
+
+For a single non-composite experiment, figure generation can be switched off by setting the analysis
+option ``plot`` to ``False``:
+
+.. jupyter-input::
+
+    experiment.analysis.set_options(plot = False)    
+
+For composite experiments, there is a ``generate_figures`` analysis option which controls how child figures are
+generated. There are three options:
+
+- ``always``: The default behavior, generate figures for each child experiment.
+- ``never``: Never generate figures for any child experiment.
+- ``selective``: Only generate figures for analysis results where ``quality`` is ``bad``. This is useful
+  for large composite experiments where you only want to examine qubits with problems.
+
+This parameter should be set on the analysis of a composite experiment before the analysis runs:
+
+.. jupyter-input::
+
+    parallel_exp = ParallelExperiment(
+        [T1(physical_qubits=(i,), delays=delays) for i in range(2)]
+    )
+    parallel_exp.analysis.set_options(generate_figures="selective")
+
+Discussion
+----------
+
+These options are useful for large composite experiments, where generating all figures incurs a significant
+overhead.
+
+See Also
+--------
+
+* The `Visualization tutorial <visualization.html>`_ discusses how to customize figures

docs/manuals/characterization/stark_experiment.rst

@@ -104,7 +104,7 @@ By default, the Stark tone is applied to the same channel as the qubit drive
 with a frequency shift. This frequency shift might update the channel frame,
 which accumulates unwanted phase against the frequency difference between
 the qubit drive :math:`f_0` and Stark tone frequencies :math:`f_S` in addition to
-the qubit Stark shfit :math:`\delta f_s`.
+the qubit Stark shift :math:`\delta f_s`.
 You can use a dedicated Stark drive channel if available.
 Otherwise, you may want to use a control channel associated with the physical
 drive port of the qubit.

docs/manuals/measurement/readout_mitigation.rst

@@ -60,7 +60,7 @@ experiments to generate the corresponding mitigators.
     num_qubits = len(qubits)
 
 Standard mitigation experiment
-==============================
+------------------------------
 
 The default mitigation experiment is *local*, meaning error probability
 is measured individually for each qubit. The experiment generates two
@@ -99,7 +99,7 @@ The individual mitigation matrices can be read off the mitigator.
         print()
 
 
-Mitigation Example
+Mitigation example
 ------------------
 
 .. jupyter-execute::

docs/manuals/verification/randomized_benchmarking.rst

@@ -161,7 +161,7 @@ for the single qubit channel :math:`n=1`. Accordingly,
 
 as a composition of depolarization from every primitive gates per qubit.
 This correction will give you two EPC values as a result of the two-qubit RB experiment.
-The corrected EPC must be closer to the outcome of of interleaved RB.
+The corrected EPC must be closer to the outcome of interleaved RB.
 The EPGs of two-qubit RB are analyzed with the corrected EPC if available.
 
 .. jupyter-execute::

docs/tutorials/calibrations.rst

@@ -34,10 +34,6 @@ This automatic updating can also be disabled using the ``auto_update`` flag.
     This tutorial requires the :mod:`qiskit_dynamics` package to run simulations.
     You can install it with ``python -m pip install qiskit-dynamics``.
 
-.. note::
-    This tutorial requires the ``pandas`` package to visualize calibration tables.
-    You can install it with ``python -m pip install pandas``.
-
 .. jupyter-execute::
 
     import pandas as pd
@@ -382,7 +378,7 @@ instruction schedule map with this over/under-rotated pulse.
     over_amp = ideal_amp*1.02
     under_amp = ideal_amp*0.98
     print(f"The reported amplitude of the X pulse is {ideal_amp:.4f} which we set as ideal_amp.") 
-    print(f"we use {over_amp:.4f} amplitude for overroation pulse and {under_amp:.4f} for underrotation pulse.")
+    print(f"we use {over_amp:.4f} amplitude for overrotation pulse and {under_amp:.4f} for underrotation pulse.")
     # build the over rotated pulse and add it to the instruction schedule map
     with pulse.build(backend=backend, name="x") as x_over:
         pulse.play(pulse.Drag(x_pulse.duration, over_amp, x_pulse.sigma, x_pulse.beta), d0)
@@ -441,7 +437,7 @@ error but also its sign.
     scale_under = target_angle / (target_angle + dtheta_under)
     print(f"The ideal angle is {target_angle:.2f} rad. We measured a deviation of {dtheta_over:.3f} rad in over-rotated pulse case.")
     print(f"Thus, scale the {over_amp:.4f} pulse amplitude by {scale_over:.3f} to obtain {over_amp*scale_over:.5f}.")
-    print(f"On the other hand, we measued a deviation of {dtheta_under:.3f} rad in under-rotated pulse case.")
+    print(f"On the other hand, we measured a deviation of {dtheta_under:.3f} rad in under-rotated pulse case.")
     print(f"Thus, scale the {under_amp:.4f} pulse amplitude by {scale_under:.3f} to obtain {under_amp*scale_under:.5f}.")
 
 

docs/tutorials/curve_analysis.rst

@@ -266,6 +266,11 @@ every logic defined in ``AnalysisA``.
 Curve Analysis workflow
 -----------------------
 
+.. warning::
+
+    :class:`CurveData` dataclass is replaced with :class:`.ScatterTable` dataframe.
+    This class will be deprecated and removed in the future release.
+
 Typically curve analysis performs fitting as follows.
 This workflow is defined in the method :meth:`CurveAnalysis._run_analysis`.
 

docs/tutorials/custom_experiment.rst

@@ -249,7 +249,7 @@ to 10.
             self._circuit = circuit        
             self._measured_qubits = measured_qubits
 
-            # Set any init optinos
+            # Set any init options
             self.set_experiment_options(num_samples=num_samples, seed=seed)
 
 Now we consider default experiment options. We choose to only let the user change
@@ -555,7 +555,7 @@ To test our code, we first simulate a noisy backend with asymmetric readout erro
 
   backend_ideal = AerSimulator()
 
-  # Backend with asymetric readout error
+  # Backend with asymmetric readout error
   p0g1 = 0.3
   p1g0 = 0.05
   noise_model = noise.NoiseModel()
@@ -588,7 +588,7 @@ Check that the experiment is appending a random Pauli and measurements as expect
     exp = RandomizedMeasurement(qc, num_samples=num_samples)
     exp.circuits()[0].draw("mpl")
 
-We now run the experiment with a GHZ circuit on an ideal backend, whic produces nearly
+We now run the experiment with a GHZ circuit on an ideal backend, which produces nearly
 perfect symmetrical results between :math:`|0000\rangle` and :math:`|1111\rangle`:
 
 .. jupyter-execute::

docs/tutorials/getting_started.rst

@@ -238,21 +238,24 @@ supports can be set:
 
   exp.set_run_options(shots=1000,
                       meas_level=MeasLevel.CLASSIFIED)
+  print(f"Shots set to {exp.run_options.get('shots')}, " 
+        "measurement level set to {exp.run_options.get('meas_level')}")
 
 Consult the documentation of the run method of your
 specific backend type for valid options.
 For example, see :meth:`qiskit_ibm_provider.IBMBackend.run` for IBM backends.
 
 Transpile options
 -----------------
-These options are passed to the Terra transpiler to transpile the experiment circuits
+These options are passed to the Qiskit :mod:`~qiskit.transpiler` to transpile the experiment circuits
 before execution:
 
 .. jupyter-execute::
 
   exp.set_transpile_options(scheduling_method='asap',
                             optimization_level=3,
                             basis_gates=["x", "sx", "rz"])
+  print(f"Transpile options are {exp.transpile_options}")
 
 Consult the documentation of :func:`qiskit.compiler.transpile` for valid options.
 
@@ -267,14 +270,15 @@ upon experiment instantiation, but can also be explicitly set via
     exp = T1(physical_qubits=(0,), delays=delays)
     new_delays=np.arange(1e-6, 600e-6, 50e-6)
     exp.set_experiment_options(delays=new_delays)
+    print(f"Experiment options are {exp.experiment_options}")
 
 Consult the :doc:`API documentation </apidocs/index>` for the options of each experiment
 class.
 
 Analysis options
 ----------------
 
-These options are unique to each analysis class. Unlike the other options, analyis
+These options are unique to each analysis class. Unlike the other options, analysis
 options are not directly set via the experiment object but use instead a method of the
 associated ``analysis``:
 
@@ -295,7 +299,7 @@ Running experiments on multiple qubits
 ======================================
 
 To run experiments across many qubits of the same device, we use **composite
-experiments**. A composite experiment is a parent object that contains one or more child
+experiments**. A :class:`.CompositeExperiment` is a parent object that contains one or more child
 experiments, which may themselves be composite. There are two core types of composite
 experiments:
 
@@ -323,7 +327,7 @@ Note that when the transpile and run options are set for a composite experiment,
 child experiments's options are also set to the same options recursively. Let's examine
 how the parallel experiment is constructed by visualizing child and parent circuits. The
 child experiments can be accessed via the
-:meth:`~.ParallelExperiment.component_experiment` method, which indexes from zero:
+:meth:`~.CompositeExperiment.component_experiment` method, which indexes from zero:
 
 .. jupyter-execute::
 
@@ -333,6 +337,16 @@ child experiments can be accessed via the
 
     parallel_exp.component_experiment(1).circuits()[0].draw(output='mpl')
 
+Similarly, the child analyses can be accessed via :meth:`.CompositeAnalysis.component_analysis` or via
+the analysis of the child experiment class:
+
+.. jupyter-execute::
+
+    parallel_exp.component_experiment(0).analysis.set_options(plot = True)
+
+    # This should print out what we set because it's the same option
+    print(parallel_exp.analysis.component_analysis(0).options.get("plot"))
+
 The circuits of all experiments assume they're acting on virtual qubits starting from
 index 0. In the case of a parallel experiment, the child experiment
 circuits are composed together and then reassigned virtual qubit indices:
@@ -393,4 +407,17 @@ into one level:
     parallel_data = parallel_exp.run(backend, seed_simulator=101).block_for_results()
 
     for result in parallel_data.analysis_results():
-        print(result)
+        print(result)
+
+Broadcasting analysis options to child experiments
+--------------------------------------------------
+
+Use the `broadcast` parameter to set analysis options to each of the child experiments.
+
+.. jupyter-execute::
+
+    parallel_exp.analysis.set_options(plot=False, broadcast=True)
+
+If the child experiment inherits from :class:`.CompositeExperiment` (such as :class:`.ParallelExperiment`
+and :class:`.BatchExperiment` classes), this process will continue to work recursively.
+In this instance, the analysis will not generate a figure for the child experiment after the analysis.