Merge remote-tracking branch 'upstream/main' into exp-data-pickle

.github/workflows/cron-staging.yml

@@ -6,6 +6,7 @@ on:
 
 jobs:
   qiskit-main-tests:
+    if: github.repository_owner == 'Qiskit-Extensions'
     name: tests-python${{ matrix.python-version }}-${{ matrix.os }}
     runs-on: ${{ matrix.os }}
     strategy:
@@ -46,6 +47,7 @@ jobs:
           TEST_TIMEOUT: 120
           OMP_NUM_THREADS: 1
   docs:
+    if: github.repository_owner == 'Qiskit-Extensions'
     name: docs
     runs-on: ubuntu-latest
     steps:

.github/workflows/docs.yml

@@ -7,6 +7,7 @@ on:
 
 jobs:
   deploy:
+    if: github.repository_owner == 'Qiskit-Extensions'
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v3

.github/workflows/docs_dev.yml

@@ -6,6 +6,7 @@ on:
 
 jobs:
   deploy:
+    if: github.repository_owner == 'Qiskit-Extensions'
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v3

.github/workflows/main.yml

@@ -11,6 +11,7 @@ concurrency:
   cancel-in-progress: true
 jobs:
   tests:
+    if: github.repository_owner == 'Qiskit-Extensions'
     name: tests-python${{ matrix.python-version }}-${{ matrix.os }}
     runs-on: ${{ matrix.os }}
     strategy:
@@ -62,6 +63,7 @@ jobs:
         run: stestr history remove all
 
   lint:
+    if: github.repository_owner == 'Qiskit-Extensions'
     name: lint
     runs-on: ubuntu-latest
     steps:
@@ -80,6 +82,7 @@ jobs:
       - name: Run lint
         run: tox -elint
   docs:
+    if: github.repository_owner == 'Qiskit-Extensions'
     name: docs
     runs-on: ubuntu-latest
     steps:

.github/workflows/neko.yml

@@ -8,6 +8,7 @@ concurrency:
   cancel-in-progress: true
 jobs:
   neko:
+    if: github.repository_owner == 'Qiskit-Extensions'
     name: Qiskit Neko Integration Tests
     runs-on: ubuntu-latest
     steps:

constraints.txt

@@ -1,4 +0,0 @@
-# Numpy 1.25 deprecated some behaviours that we used, and caused some
-# tests to flake. See https://github.com/Qiskit/qiskit/issues/10305,
-# remove pin when resolving that.
-numpy<1.25

docs/howtos/cloud_service.rst

@@ -4,7 +4,7 @@ Save and load experiment data with the cloud service
 .. note::
     This guide is only for those who have access to the cloud service. You can 
     check whether you do by logging into the IBM Quantum interface 
-    and seeing if you can see the `database <https://quantum-computing.ibm.com/experiments>`__.
+    and seeing if you can see the `database <https://quantum.ibm.com/experiments>`__.
 
 Problem
 -------
@@ -44,13 +44,13 @@ backend and not a simulator to be able to save the experiment data. This is done
 .. jupyter-output::
 
     You can view the experiment online at 
-    https://quantum-computing.ibm.com/experiments/10a43cb0-7cb9-41db-ad74-18ea6cf63704
+    https://quantum.ibm.com/experiments/10a43cb0-7cb9-41db-ad74-18ea6cf63704
 
 Loading
 ~~~~~~~
 
 Let's load a `previous T1
-experiment <https://quantum-computing.ibm.com/experiments/9640736e-d797-4321-b063-d503f8e98571>`__ 
+experiment <https://quantum.ibm.com/experiments/9640736e-d797-4321-b063-d503f8e98571>`__ 
 (requires login to view), which we've made public by editing the ``Share level`` field:
 
 .. jupyter-input::
@@ -59,13 +59,11 @@ experiment <https://quantum-computing.ibm.com/experiments/9640736e-d797-4321-b06
     service = ExperimentData.get_service_from_backend(backend)
     load_expdata = ExperimentData.load("9640736e-d797-4321-b063-d503f8e98571", service)
 
-To display the figure, which is serialized into a string, we need the
-``SVG`` library:
+Now we can display the figure from the loaded experiment data:
 
 .. jupyter-input::
 
-    from IPython.display import SVG
-    SVG(load_expdata.figure(0).figure)
+    load_expdata.figure(0)
 
 .. image:: ./experiment_cloud_service/t1_loaded.png
 
@@ -143,7 +141,7 @@ The :meth:`~.ExperimentData.auto_save` feature automatically saves changes to th
 
 .. jupyter-output::
 
-    You can view the experiment online at https://quantum-computing.ibm.com/experiments/cdaff3fa-f621-4915-a4d8-812d05d9a9ca
+    You can view the experiment online at https://quantum.ibm.com/experiments/cdaff3fa-f621-4915-a4d8-812d05d9a9ca
     <ExperimentData[T1], backend: ibmq_lima, status: ExperimentStatus.DONE, experiment_id: cdaff3fa-f621-4915-a4d8-812d05d9a9ca>
 
 Setting ``auto_save = True`` works by triggering :meth:`.ExperimentData.save`.
@@ -188,5 +186,5 @@ Web interface
 ~~~~~~~~~~~~~
 
 You can also view experiment results as well as change the tags and share level at the `IBM Quantum Experiments
-pane <https://quantum-computing.ibm.com/experiments?date_interval=last-90-days&owner=me>`__
+pane <https://quantum.ibm.com/experiments?date_interval=last-90-days&owner=me>`__
 on the cloud.

docs/howtos/experiment_times.rst

@@ -24,7 +24,7 @@ are all of type ``datetime.datetime`` and in your local timezone:
 .. note::
     The below attributes are only relevant for those who have access to the cloud service. You can 
     check whether you do by logging into the IBM Quantum interface 
-    and seeing if you can see the `database <https://quantum-computing.ibm.com/experiments>`__.
+    and seeing if you can see the `database <https://quantum.ibm.com/experiments>`__.
 
 - :attr:`.ExperimentData.creation_datetime` is the time when the experiment data was saved via the
   service. This defaults to ``None`` if experiment data has not yet been saved.

docs/howtos/rerun_analysis.rst

@@ -37,12 +37,14 @@ job IDs:
 
     expdata = ExperimentData(experiment = experiment)
     expdata.add_jobs([provider.retrieve_job(job_id) for job_id in job_ids])
-    experiment.analysis.run(expdata)
+    experiment.analysis.run(expdata, replace_results=True)
 
     # Block execution of subsequent code until analysis is complete
     expdata.block_for_results()
 
-``expdata`` will be the new experiment data object containing results of the rerun analysis.
+``expdata`` will be the new experiment data object containing results of the rerun analysis. Note that if
+``replace_results`` isn't set, running the analysis will return a new :class:`.ExperimentData` object
+instead of overwriting the existing one.
 
 If you have the job data in the form of a :class:`~qiskit.result.Result` object, you can
 invoke the :meth:`.add_data` method instead of :meth:`.add_jobs`:
@@ -66,7 +68,7 @@ contain correct results.
 
 In the case where jobs are not directly accessible from the provider but you've
 downloaded the jobs from the 
-`IQS dashboard <https://quantum-computing.ibm.com/jobs>`_, you can load them from
+`IQS dashboard <https://quantum.ibm.com/jobs>`_, you can load them from
 the downloaded directory into :class:`~qiskit.result.Result` objects with this code:
 
 .. jupyter-input::
@@ -115,7 +117,7 @@ first component experiment.
 
     data = ExperimentData(experiment=pexp)
     data.add_jobs([provider.retrieve_job(job_id) for job_id in job_ids])
-    pexp.analysis.run(data)
+    pexp.analysis.run(data, replace_results=True)
 
 See Also
 --------

docs/howtos/runtime_sessions.rst

@@ -5,7 +5,7 @@ Problem
 -------
 
 You want to run experiments in a `Runtime session
-<https://qiskit.org/ecosystem/ibm-runtime/sessions.html>`_ so that jobs can run in close temporal proximity.
+<https://docs.quantum.ibm.com/run/sessions>`_ so that jobs can run in close temporal proximity.
 
 Solution
 --------

docs/tutorials/calibrations.rst

@@ -12,9 +12,8 @@ measurement data manually.
 In this tutorial, we demonstrate how to calibrate single-qubit gates using the
 calibration framework in Qiskit Experiments. We will run experiments on our test pulse
 backend, :class:`.SingleTransmonTestBackend`, a backend that simulates the underlying
-pulses with `Qiskit Dynamics <https://qiskit.org/documentation/dynamics/>`_ on a
-three-level model of a transmon. You can also run these experiments on any real backend
-with Pulse enabled (see
+pulses with :mod:`qiskit_dynamics` on a three-level model of a transmon. You can also
+run these experiments on any real backend with Pulse enabled (see
 :external+qiskit:doc:`tutorials/circuits_advanced/08_gathering_system_information`).
 
 We will run experiments to 
@@ -196,8 +195,8 @@ Run the calibration experiment:
 
 The instance of ``calibrations`` has been automatically updated with the measured
 frequency, as shown below. In addition to the columns shown below, ``calibrations`` also
-store the group to which a value belongs, whether a values is valid or not and the
-experiment id that produce a value.
+stores the group to which a value belongs, whether a value is valid or not, and the
+experiment id that produced a value.
 
 .. jupyter-execute::
 

qiskit_experiments/calibration_management/__init__.py

@@ -23,7 +23,7 @@
     otherwise indicated.
 
 Calibrating qubit setups is the task of finding the pulse shapes and parameter
-values that maximizes the fidelity of the resulting quantum operations. This
+values that maximize the fidelity of the resulting quantum operations. This
 therefore requires experiments which are analyzed to extract parameter values.
 Furthermore, the resulting parameter values and schedules must be managed. The
 calibration management module in Qiskit experiments allows users to manage

qiskit_experiments/calibration_management/calibrations.py

@@ -1270,12 +1270,12 @@ def schedules(self) -> List[Dict[str, Any]]:
         Returns:
             data: A list of dictionaries with all the schedules in it. The key-value pairs are
 
-                * 'qubits': the qubits to which this schedule applies. This may be an empty
-                  tuple () if the schedule is the default for all qubits.
-                * 'schedule': The schedule.
-                * 'parameters': The parameters in the schedule exposed for convenience.
+            * ``qubits``: the qubits to which this schedule applies. This may be an empty
+                tuple () if the schedule is the default for all qubits.
+            * ``schedule``: The schedule.
+            * ``parameters``: The parameters in the schedule exposed for convenience.
 
-                This list of dictionaries can easily be converted to a data frame.
+            This list of dictionaries can easily be converted to a data frame.
         """
         data = []
         for key, sched in self._schedules.items():

qiskit_experiments/framework/analysis_result_table.py

@@ -85,13 +85,14 @@ def filter_columns(self, columns: Union[str, List[str]]) -> List[str]:
 
         Args:
             columns: Specifying a set of columns to return. You can pass a list of each
-                column name to return, otherwise builtin column groups are available.
+                column name to return, otherwise builtin column groups are available:
+
+                * ``all``: Return all columns, including metadata to communicate
+                  with experiment service, such as entry IDs.
+                * ``default``: Return columns including analysis result with supplementary
+                  information about experiment.
+                * ``minimal``: Return only analysis subroutine returns.
 
-                    * "all": Return all columns, including metadata to communicate
-                        with experiment service, such as entry IDs.
-                    * "default": Return columns including analysis result with supplementary
-                        information about experiment.
-                    * "minimal": Return only analysis subroutine returns.
 
         Raises:
             ValueError: When column is given in string which doesn't match with any builtin group.

qiskit_experiments/framework/experiment_data.py

@@ -67,6 +67,7 @@
     ExperimentDataSaveFailed,
 )
 
+
 if TYPE_CHECKING:
     # There is a cyclical dependency here, but the name needs to exist for
     # Sphinx on Python 3.9+ to link type hints correctly.  The gating on
@@ -192,7 +193,7 @@ def _repr_svg_(self):
         if isinstance(self.figure, str):
             return self.figure
         if isinstance(self.figure, bytes):
-            return str(self.figure)
+            return self.figure.decode("utf-8")
         return None
 
 
@@ -205,7 +206,7 @@ class ExperimentData:
     .. note::
         Saving experiment data to the cloud database is currently a limited access feature. You can
         check whether you have access by logging into the IBM Quantum interface
-        and seeing if you can see the `database <https://quantum-computing.ibm.com/experiments>`__.
+        and seeing if you can see the `database <https://quantum.ibm.com/experiments>`__.
 
     This class handles the following:
 
@@ -1071,6 +1072,13 @@ def _retrieve_data(self):
         """Retrieve job data if missing experiment data."""
         # Get job results if missing in experiment data.
         if self.provider is None:
+            # 'self._result_data' could be locked, so I check a copy of it.
+            if not self._result_data.copy():
+                # Adding warning so the user will have indication why the analysis may fail.
+                LOG.warning(
+                    "Provider for ExperimentData object doesn't exist, resulting in a failed attempt to"
+                    " retrieve data from the server; no stored result data exists"
+                )
             return
         retrieved_jobs = {}
         jobs_to_retrieve = []  # the list of all jobs to retrieve from the server
@@ -1528,25 +1536,25 @@ def analysis_results(
             index: Index of the analysis result to be returned.
                 Several types are accepted for convenience:
 
-                    * None: Return all analysis results.
-                    * int: Specific index of the analysis results.
-                    * slice: A list slice of indexes.
-                    * str: ID or name of the analysis result.
+                * None: Return all analysis results.
+                * int: Specific index of the analysis results.
+                * slice: A list slice of indexes.
+                * str: ID or name of the analysis result.
 
             refresh: Retrieve the latest analysis results from the server, if
                 an experiment service is available.
-            block: If True block for any analysis callbacks to finish running.
+            block: If ``True``, block for any analysis callbacks to finish running.
             timeout: max time in seconds to wait for analysis callbacks to finish running.
             columns: Specifying a set of columns to return. You can pass a list of each
-                column name to return, otherwise builtin column groups are available.
+                column name to return, otherwise builtin column groups are available:
 
-                    * "all": Return all columns, including metadata to communicate
-                        with experiment service, such as entry IDs.
-                    * "default": Return columns including analysis result with supplementary
-                        information about experiment.
-                    * "minimal": Return only analysis subroutine returns.
+                * ``all``: Return all columns, including metadata to communicate
+                  with the experiment service, such as entry IDs.
+                * ``default``: Return columns including analysis result with supplementary
+                  information about experiment.
+                * ``minimal``: Return only analysis subroutine returns.
 
-            dataframe: Set True to return analysis results in the dataframe format.
+            dataframe: Set to ``True`` to return analysis results in the dataframe format.
 
         Returns:
             Analysis results for this experiment.
@@ -1681,7 +1689,7 @@ def save(
 
         Args:
             suppress_errors: should the method catch exceptions (true) or
-            pass them on, potentially aborting the experiment (false)
+                pass them on, potentially aborting the experiment (false)
             max_workers: Maximum number of concurrent worker threads (capped by 10)
             save_figures: Whether to save figures in the database or not
             save_children: For composite experiments, whether to save children as well
@@ -1779,7 +1787,7 @@ def save(
         if not self.service.local and self.verbose:
             print(
                 "You can view the experiment online at "
-                f"https://quantum-computing.ibm.com/experiments/{self.experiment_id}"
+                f"https://quantum.ibm.com/experiments/{self.experiment_id}"
             )
         # handle children, but without additional prints
         if save_children:
@@ -2293,6 +2301,7 @@ def copy(self, copy_results: bool = True) -> "ExperimentData":
         new_instance = ExperimentData(
             backend=self.backend,
             service=self.service,
+            provider=self.provider,
             parent_id=self.parent_id,
             job_ids=self.job_ids,
             child_data=list(self._child_data.values()),
@@ -2523,7 +2532,7 @@ def get_service_from_backend(backend):
     @staticmethod
     def get_service_from_provider(provider):
         """Initializes the service from the provider data"""
-        db_url = "https://auth.quantum-computing.ibm.com/api"
+        db_url = "https://auth.quantum.ibm.com/api"
         try:
             # qiskit-ibmq-provider style
             if hasattr(provider, "credentials"):

qiskit_experiments/library/calibration/fine_frequency_cal.py

@@ -123,7 +123,7 @@ def update_calibrations(self, experiment_data: ExperimentData):
 
         The frequency of the qubit is updated according to
 
-        ..math::
+        .. math::
 
             f \to f - \frac{{\rm d}\theta}{2\pi\tau{\rm d}t}
 

qiskit_experiments/library/calibration/half_angle_cal.py

@@ -130,7 +130,7 @@ def update_calibrations(self, experiment_data: ExperimentData):
         in the complex amplitude of the pulse. The update rule for the half angle calibration is
         therefore:
 
-        ..math::
+        .. math::
 
             A \to A \cdot e^{-i{\rm d}\theta_\text{hac}/2}
 

qiskit_experiments/library/characterization/analysis/correlated_readout_error_analysis.py

@@ -33,7 +33,7 @@ class CorrelatedReadoutErrorAnalysis(BaseAnalysis):
         :math:`A` is a :math:`2^n\times 2^n` matrix :math:`A` such that :math:`A_{y,x}`
         is the probability to observe :math:`y` given the true outcome should be :math:`x`.
 
-        In the experiment, for each :math:`x`a circuit is constructed whose expected
+        In the experiment, for each :math:`x` a circuit is constructed whose expected
         outcome is :math:`x`. From the observed results on the circuit, the probability for
         each :math:`y` is determined, and :math:`A_{y,x}` is set accordingly.
 

qiskit_experiments/library/characterization/rabi.py

@@ -187,7 +187,7 @@ def _metadata(self):
 
 class EFRabi(Rabi):
     r"""An experiment that scans the amplitude of a pulse inducing rotations on the
-     :math:`|1\rangle` <-> :math:`|2\rangle` transition.
+    :math:`|1\rangle` <-> :math:`|2\rangle` transition.
 
     # section: overview