Remove code deprecated in 0.9

The following parts of the code deprecated in 0.9 are removed here:

* `PulseBackend` and `SingleTransmonTestBackend`
* `RestlessNode`, `RestToCounts`, and `RestlessToIQ`
* The curve analysis `utils` functions `data_sort`, `filter_data`,
  `mean_xy_data`, and `multi_mean_xy_data`
* The `ScatterTable` methods/attributes `data_allocation`, `labels`, and
  `get_subset_of`

0.9 was released on March 18, 2025, so these removals should not be
released until June 18th according to the deprecation policy.

Author: wshanks

docs/conf.py

@@ -161,7 +161,6 @@
     "uncertainties": ("https://pythonhosted.org/uncertainties", None),
     "pandas": ("http://pandas.pydata.org/docs/", None),
     "qiskit_aer": ("https://qiskit.github.io/qiskit-aer/", None),
-    "qiskit_dynamics": ("https://qiskit-community.github.io/qiskit-dynamics/", None),
     "qiskit_ibm_runtime": ("https://docs.quantum.ibm.com/api/qiskit-ibm-runtime/", None),
 }
 

docs/tutorials/visualization.rst

@@ -34,25 +34,9 @@ Generating and customizing a figure using a plotter
 First, we display the default figure from a :class:`.T1` experiment as a starting point:
 
 .. note::
-    This tutorial requires the :mod:`qiskit_dynamics`, :external+qiskit_aer:doc:`qiskit-aer <index>`, and
-    :external+qiskit_ibm_runtime:doc:`qiskit-ibm-runtime <index>` packages to run simulations.  You can install them
-    with ``python -m pip install qiskit-dynamics qiskit-aer qiskit-ibm-runtime``.
-
-.. jupyter-execute::
-    :hide-code:
-
-    import warnings
-
-    warnings.filterwarnings(
-        "ignore",
-        message=".*Due to the deprecation of Qiskit Pulse.*",
-        category=DeprecationWarning,
-    )
-    warnings.filterwarnings(
-        "ignore",
-        message=".*The entire Qiskit Pulse package is being deprecated.*",
-        category=DeprecationWarning,
-    )
+    This tutorial requires the :external+qiskit_aer:doc:`qiskit-aer <index>`
+    package to run simulations.  You can install it
+    with ``python -m pip install qiskit-aer``.
 
 .. jupyter-execute::
 

qiskit_experiments/curve_analysis/__init__.py

@@ -93,13 +93,9 @@
 
     utils.analysis_result_to_repr
     utils.convert_lmfit_result
-    utils.data_sort
     utils.eval_with_uncertainties
-    utils.filter_data
     utils.inverse_weighted_variance
     utils.is_error_not_significant
-    utils.mean_xy_data
-    utils.multi_mean_xy_data
     utils.level2_probability
     utils.probability
     utils.sample_average
@@ -115,10 +111,6 @@
     FitOptions,
     ParameterRepr,
 )
-from .curve_fit import (
-    process_curve_data,
-    process_multi_curve_data,
-)
 from . import guess
 from . import fit_function
 from . import utils

qiskit_experiments/curve_analysis/curve_fit.py

@@ -23,8 +23,6 @@
 import numpy as np
 import pandas as pd
 
-from qiskit.utils import deprecate_func
-
 
 LOG = logging.getLogger(__name__)
 
@@ -406,46 +404,6 @@ def _warn_composite_data(self):
                 UserWarning,
             )
 
-    @property
-    @deprecate_func(
-        since="0.9",
-        additional_msg="Curve data uses dataframe representation. Call .series_id instead.",
-        package_name="qiskit-experiments",
-        is_property=True,
-    )
-    def data_allocation(self) -> np.ndarray:
-        """Index of corresponding fit model."""
-        return self.series_id
-
-    @property
-    @deprecate_func(
-        since="0.9",
-        additional_msg="No alternative is provided. Use .series_name with set operation.",
-        package_name="qiskit-experiments",
-        is_property=True,
-    )
-    def labels(self) -> list[str]:
-        """List of model names."""
-        # Order sensitive
-        name_id_tups = self.dataframe.groupby(["series_name", "series_id"]).groups.keys()
-        return [k[0] for k in sorted(name_id_tups, key=lambda k: k[1])]
-
-    @deprecate_func(
-        since="0.9",
-        additional_msg="Use filter method instead.",
-        package_name="qiskit-experiments",
-    )
-    def get_subset_of(self, index: str | int) -> "ScatterTable":
-        """Filter data by series name or index.
-
-        Args:
-            index: Series index of name.
-
-        Returns:
-            A subset of data corresponding to a particular series.
-        """
-        return self.filter(series=index)
-
     def __len__(self):
         """Return the number of data points stored in the table."""
         return len(self.dataframe)