Handle test incompatibilities with Qiskit 1.3 (qiskit-community#1478)

These changes should get the daily test run against Qiskit main passing again for now. The necessary changes were: * Specify `num_qubits` for the `SingleTransmonTestBackend` target which now must match the number of qubit properties passed. * Only convert deprecation warnings to errors in the tests when the warning appears to be triggered by qiskit-experiments code. Qiskit 1.3 triggers new deprecation warnings by calling its own deprecated code internally and the Experiments tests either need to ignore those lower level warnings globally or individually each time they come up. Here they are just ignored globally. * Ignore deprecation warnings related to Qiskit Pulse. There are many of these and they need to be addressed, but there is too much work to address them, so they are ignored in favor of being to catch other errors in the tests. * Ignore some deprecated usage of Experiments code in the tests. As part of reworking which warnings are converted to errors warnings triggered by the test code are now converted to errors. Previously only warnings triggered by the `qiskit_experiments` package or deprecation warnings were converted to errors. The few new cases that were surfaced were explicitly testing deprecated functions, so those cases were ignored. * Regenerate the quantum volume expected results. Qiskit 1.3 has a reworked quantum volume function that generates different circuits than Qiskit 1.2 for a given seed number. * Modify an RB test that was checking that RB code gave an error when a target was missing a gate that the experiment wanted to interleave. The test was implemented by deleting an instruction from the target but with Qiskit 1.3 the target is less mutable, so a new target needed to be constructed without the instruction rather than deleting it from a larger target. * Ignore warnings about Qiskit Pulse and internal Qiskit deprecations in the jupyter-sphinx documentation.
wshanks · Nov 5, 2024 · 05d7487 · 05d7487
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diff --git a/docs/manuals/characterization/stark_experiment.rst b/docs/manuals/characterization/stark_experiment.rst
@@ -160,6 +160,11 @@ by a variant of the Hahn-echo pulse sequence [5]_.
         message=".*Due to the deprecation of Qiskit Pulse.*",
         category=DeprecationWarning,
     )
+    warnings.filterwarnings(
+        "ignore",
+        message=".*The entire Qiskit Pulse package is being deprecated.*",
+        category=DeprecationWarning,
+    )
 
     from qiskit_experiments.library import StarkRamseyXY
     from qiskit import schedule, pulse

diff --git a/docs/manuals/measurement/restless_measurements.rst b/docs/manuals/measurement/restless_measurements.rst
@@ -77,6 +77,16 @@ they use always starts with the qubits in the ground state.
         message=".*Support for restless.*",
         category=DeprecationWarning,
     )
+    warnings.filterwarnings(
+        "ignore",
+        message=".*The entire Qiskit Pulse package is being deprecated.*",
+        category=DeprecationWarning,
+    )
+    warnings.filterwarnings(
+        "ignore",
+        message=".*QuantumCircuit.duration.*",
+        category=DeprecationWarning,
+    )
 
     # Temporary workaround for missing support in Qiskit and qiskit-ibm-runtime
     from qiskit_experiments.test.patching import patch_sampler_test_support

diff --git a/docs/tutorials/calibrations.rst b/docs/tutorials/calibrations.rst
@@ -51,6 +51,11 @@ This automatic updating can also be disabled using the ``auto_update`` flag.
         message=".*Due to the deprecation of Qiskit Pulse.*",
         category=DeprecationWarning,
     )
+    warnings.filterwarnings(
+        "ignore",
+        message=".*The entire Qiskit Pulse package is being deprecated.*",
+        category=DeprecationWarning,
+    )
 
 .. jupyter-execute::
 

diff --git a/docs/tutorials/data_processor.rst b/docs/tutorials/data_processor.rst
@@ -78,6 +78,11 @@ The code below sets up the Rabi experiment.
         message=".*Due to the deprecation of Qiskit Pulse.*",
         category=DeprecationWarning,
     )
+    warnings.filterwarnings(
+        "ignore",
+        message=".*The entire Qiskit Pulse package is being deprecated.*",
+        category=DeprecationWarning,
+    )
 
 .. jupyter-execute::
 

diff --git a/docs/tutorials/visualization.rst b/docs/tutorials/visualization.rst
@@ -48,6 +48,11 @@ First, we display the default figure from a :class:`.Rabi` experiment as a start
         message=".*Due to the deprecation of Qiskit Pulse.*",
         category=DeprecationWarning,
     )
+    warnings.filterwarnings(
+        "ignore",
+        message=".*The entire Qiskit Pulse package is being deprecated.*",
+        category=DeprecationWarning,
+    )
 
 .. jupyter-execute::
 

diff --git a/qiskit_experiments/library/characterization/drag.py b/qiskit_experiments/library/characterization/drag.py
@@ -77,6 +77,11 @@ class RoughDrag(BaseExperiment, RestlessMixin):
                 message=".*Due to the deprecation of Qiskit Pulse.*",
                 category=DeprecationWarning,
             )
+            warnings.filterwarnings(
+                "ignore",
+                message=".*The entire Qiskit Pulse package is being deprecated.*",
+                category=DeprecationWarning,
+            )
 
             # backend
             from qiskit_experiments.test.pulse_backend import SingleTransmonTestBackend

diff --git a/qiskit_experiments/library/characterization/rabi.py b/qiskit_experiments/library/characterization/rabi.py
@@ -69,6 +69,11 @@ class Rabi(BaseExperiment, RestlessMixin):
                 message=".*Due to the deprecation of Qiskit Pulse.*",
                 category=DeprecationWarning,
             )
+            warnings.filterwarnings(
+                "ignore",
+                message=".*The entire Qiskit Pulse package is being deprecated.*",
+                category=DeprecationWarning,
+            )
 
             # backend
             from qiskit_experiments.test.pulse_backend import SingleTransmonTestBackend
@@ -254,6 +259,11 @@ class EFRabi(Rabi):
                 message=".*Due to the deprecation of Qiskit Pulse.*",
                 category=DeprecationWarning,
             )
+            warnings.filterwarnings(
+                "ignore",
+                message=".*The entire Qiskit Pulse package is being deprecated.*",
+                category=DeprecationWarning,
+            )
 
             # backend
             from qiskit_experiments.test.pulse_backend import SingleTransmonTestBackend

diff --git a/qiskit_experiments/test/pulse_backend.py b/qiskit_experiments/test/pulse_backend.py
@@ -603,6 +603,7 @@ def __init__(
             }
         )
         self._target = Target(
+            num_qubits=1,
             qubit_properties=[QubitProperties(frequency=qubit_frequency)],
             dt=self.dt,
             granularity=16,

diff --git a/test/base.py b/test/base.py
@@ -111,11 +111,11 @@ def setUpClass(cls):
 
             patch_sampler_test_support()
 
-            warnings.filterwarnings("error", category=DeprecationWarning)
             # Tests should not generate any warnings unless testing those
             # warnings. In that case, the test should catch the warning
             # assertWarns or warnings.catch_warnings.
             warnings.filterwarnings("error", module="qiskit_experiments")
+            warnings.filterwarnings("error", module=r"test\.")
             # Ideally, changes introducing pending deprecations should include
             # alternative code paths and not need to generate warnings in the
             # tests but until this exception is necessary until the use of the
@@ -176,6 +176,7 @@ def setUpClass(cls):
                 ".*qiskit.providers.models.backendproperties.BackendProperties.*",
                 ".*qiskit.providers.fake_provider.fake_backend.FakeBackend.*",
                 ".*qiskit.providers.backend.BackendV1.*",
+                ".*The entire Qiskit Pulse package is being deprecated.*",
             ]
             for msg in allow_deprecationwarning_message:
                 warnings.filterwarnings("default", category=DeprecationWarning, message=msg)

diff --git a/test/curve_analysis/test_baseclass.py b/test/curve_analysis/test_baseclass.py
@@ -13,6 +13,8 @@
 # pylint: disable=invalid-name
 
 """Test curve fitting base class."""
+import warnings
+
 from test.base import QiskitExperimentsTestCase
 from test.fake_experiment import FakeExperiment
 
@@ -139,22 +141,26 @@ def test_data_extraction(self):
             },
         )
 
-        curve_data = analysis._run_data_processing(raw_data=expdata1.data() + expdata2.data())
-        self.assertListEqual(curve_data.labels, ["s1", "s2"])
-
-        # check data of series1
-        sub1 = curve_data.get_subset_of("s1")
-        self.assertListEqual(sub1.labels, ["s1"])
-        np.testing.assert_array_equal(sub1.x, x)
-        np.testing.assert_array_almost_equal(sub1.y, y1, decimal=3)
-        np.testing.assert_array_equal(sub1.data_allocation, np.full(x.size, 0))
-
-        # check data of series2
-        sub2 = curve_data.get_subset_of("s2")
-        self.assertListEqual(sub2.labels, ["s2"])
-        np.testing.assert_array_equal(sub2.x, x)
-        np.testing.assert_array_almost_equal(sub2.y, y2, decimal=3)
-        np.testing.assert_array_equal(sub2.data_allocation, np.full(x.size, 1))
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", message=".*ScatterTable.labels.*")
+            warnings.filterwarnings("ignore", message=".*ScatterTable.get_subset_of.*")
+            warnings.filterwarnings("ignore", message=".*ScatterTable.data_allocation.*")
+            curve_data = analysis._run_data_processing(raw_data=expdata1.data() + expdata2.data())
+            self.assertListEqual(curve_data.labels, ["s1", "s2"])
+
+            # check data of series1
+            sub1 = curve_data.get_subset_of("s1")
+            self.assertListEqual(sub1.labels, ["s1"])
+            np.testing.assert_array_equal(sub1.x, x)
+            np.testing.assert_array_almost_equal(sub1.y, y1, decimal=3)
+            np.testing.assert_array_equal(sub1.data_allocation, np.full(x.size, 0))
+
+            # check data of series2
+            sub2 = curve_data.get_subset_of("s2")
+            self.assertListEqual(sub2.labels, ["s2"])
+            np.testing.assert_array_equal(sub2.x, x)
+            np.testing.assert_array_almost_equal(sub2.y, y2, decimal=3)
+            np.testing.assert_array_equal(sub2.data_allocation, np.full(x.size, 1))
 
     def test_create_result(self):
         """A testcase for creating analysis result data from fit data."""

diff --git a/test/curve_analysis/test_curve_fitting.py b/test/curve_analysis/test_curve_fitting.py
@@ -11,6 +11,8 @@
 # that they have been altered from the originals.
 
 """Test version string generation."""
+import warnings
+
 from test.base import QiskitExperimentsTestCase
 import numpy as np
 
@@ -88,55 +90,77 @@ def test_process_curve_data(self):
     def test_mean_xy_data(self):
         """Test mean_xy_data function"""
         # pylint: disable=unbalanced-tuple-unpacking
-        x = np.array([1, 1, 1, 2, 2, 2, 2, 3, 3, 4, 5, 5, 5, 5])
-        y = np.array([1, 2, 3, 8, 10, 50, 60, 10, 11, 17, 10, 10, 10, 10])
-        x_mean, y_mean, y_sigma, _ = mean_xy_data(x, y, method="sample")
-
-        expected_x_mean = np.array([1, 2, 3, 4, 5])
-        expected_y_mean = np.array([2, 32, 10.5, 17, 10])
-        expected_y_sigma = np.sqrt(np.array([2 / 9, 542 / 4, 0.25 / 2, 0, 0]))
-        self.assertTrue(np.allclose(expected_x_mean, x_mean), msg=f"{x_mean} != {expected_x_mean}")
-        self.assertTrue(np.allclose(expected_y_mean, y_mean), msg=f"{y_mean} != {expected_y_mean}")
-        self.assertTrue(
-            np.allclose(expected_y_sigma, y_sigma), msg=f"{y_sigma} != {expected_y_sigma}"
-        )
-
-        sigma = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14])
-        x_mean, y_mean, y_sigma, _ = mean_xy_data(x, y, sigma, method="iwv")
-        expected_y_mean = np.array([1.34693878, 23.31590234, 10.44137931, 17.0, 10.0])
-        expected_y_sigma = np.array([0.85714286, 2.57610543, 5.97927455, 10.0, 6.17470935])
-        self.assertTrue(np.allclose(expected_x_mean, x_mean), msg=f"{x_mean} != {expected_x_mean}")
-        self.assertTrue(np.allclose(expected_y_mean, y_mean), msg=f"{y_mean} != {expected_y_mean}")
-        self.assertTrue(
-            np.allclose(expected_y_sigma, y_sigma), msg=f"{y_sigma} != {expected_y_sigma}"
-        )
-
-        sigma = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14])
-        shots = np.array([10, 20, 10, 30, 20, 10, 40, 10, 10, 20, 30, 20, 30, 10])
-        x_mean, y_mean, y_sigma, y_shots = mean_xy_data(x, y, sigma, shots, method="shots_weighted")
-        expected_y_mean = np.array([2.0, 33.4, 10.5, 17.0, 10.0])
-        expected_y_sigma = np.array([1.27475488, 3.26190129, 6.02079729, 10.0, 6.46166282])
-        expected_y_shots = np.array([40, 100, 20, 20, 90])
-        self.assertTrue(np.allclose(expected_x_mean, x_mean), msg=f"{x_mean} != {expected_x_mean}")
-        self.assertTrue(np.allclose(expected_y_mean, y_mean), msg=f"{y_mean} != {expected_y_mean}")
-        self.assertTrue(
-            np.allclose(expected_y_sigma, y_sigma), msg=f"{y_sigma} != {expected_y_sigma}"
-        )
-        self.assertTrue(
-            np.allclose(expected_y_shots, y_shots), msg=f"{y_shots} != {expected_y_shots}"
-        )
-
-        x = np.array([1, 1, 1, 1, 2, 2, 2, 2])
-        y = np.array([2, 6, 100, 200, 17, 50, 60, 70])
-        series = np.array([0, 0, 1, 1, 0, 1, 1, 1])
-        series, x_mean, y_mean, y_sigma, _ = multi_mean_xy_data(series, x, y, method="sample")
-        expected_x_mean = np.array([1, 2, 1, 2])
-        expected_y_mean = np.array([4, 17, 150, 60])
-        expected_y_sigma = np.sqrt(np.array([4.0 / 2, 0.0 / 1, 2500.0 / 2, 66.66666667 / 3]))
-        expected_series = np.array([0, 0, 1, 1])
-        self.assertTrue(np.allclose(expected_x_mean, x_mean), msg=f"{x_mean} != {expected_x_mean}")
-        self.assertTrue(np.allclose(expected_y_mean, y_mean), msg=f"{y_mean} != {expected_y_mean}")
-        self.assertTrue(
-            np.allclose(expected_y_sigma, y_sigma), msg=f"{y_sigma} != {expected_y_sigma}"
-        )
-        self.assertTrue(np.allclose(expected_series, series), msg=f"{series} != {expected_series}")
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", message=".*mean_xy_data.*")
+            x = np.array([1, 1, 1, 2, 2, 2, 2, 3, 3, 4, 5, 5, 5, 5])
+            y = np.array([1, 2, 3, 8, 10, 50, 60, 10, 11, 17, 10, 10, 10, 10])
+            x_mean, y_mean, y_sigma, _ = mean_xy_data(x, y, method="sample")
+
+            expected_x_mean = np.array([1, 2, 3, 4, 5])
+            expected_y_mean = np.array([2, 32, 10.5, 17, 10])
+            expected_y_sigma = np.sqrt(np.array([2 / 9, 542 / 4, 0.25 / 2, 0, 0]))
+            self.assertTrue(
+                np.allclose(expected_x_mean, x_mean), msg=f"{x_mean} != {expected_x_mean}"
+            )
+            self.assertTrue(
+                np.allclose(expected_y_mean, y_mean), msg=f"{y_mean} != {expected_y_mean}"
+            )
+            self.assertTrue(
+                np.allclose(expected_y_sigma, y_sigma), msg=f"{y_sigma} != {expected_y_sigma}"
+            )
+
+            sigma = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14])
+            x_mean, y_mean, y_sigma, _ = mean_xy_data(x, y, sigma, method="iwv")
+            expected_y_mean = np.array([1.34693878, 23.31590234, 10.44137931, 17.0, 10.0])
+            expected_y_sigma = np.array([0.85714286, 2.57610543, 5.97927455, 10.0, 6.17470935])
+            self.assertTrue(
+                np.allclose(expected_x_mean, x_mean), msg=f"{x_mean} != {expected_x_mean}"
+            )
+            self.assertTrue(
+                np.allclose(expected_y_mean, y_mean), msg=f"{y_mean} != {expected_y_mean}"
+            )
+            self.assertTrue(
+                np.allclose(expected_y_sigma, y_sigma), msg=f"{y_sigma} != {expected_y_sigma}"
+            )
+
+            sigma = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14])
+            shots = np.array([10, 20, 10, 30, 20, 10, 40, 10, 10, 20, 30, 20, 30, 10])
+            x_mean, y_mean, y_sigma, y_shots = mean_xy_data(
+                x, y, sigma, shots, method="shots_weighted"
+            )
+            expected_y_mean = np.array([2.0, 33.4, 10.5, 17.0, 10.0])
+            expected_y_sigma = np.array([1.27475488, 3.26190129, 6.02079729, 10.0, 6.46166282])
+            expected_y_shots = np.array([40, 100, 20, 20, 90])
+            self.assertTrue(
+                np.allclose(expected_x_mean, x_mean), msg=f"{x_mean} != {expected_x_mean}"
+            )
+            self.assertTrue(
+                np.allclose(expected_y_mean, y_mean), msg=f"{y_mean} != {expected_y_mean}"
+            )
+            self.assertTrue(
+                np.allclose(expected_y_sigma, y_sigma), msg=f"{y_sigma} != {expected_y_sigma}"
+            )
+            self.assertTrue(
+                np.allclose(expected_y_shots, y_shots), msg=f"{y_shots} != {expected_y_shots}"
+            )
+
+            x = np.array([1, 1, 1, 1, 2, 2, 2, 2])
+            y = np.array([2, 6, 100, 200, 17, 50, 60, 70])
+            series = np.array([0, 0, 1, 1, 0, 1, 1, 1])
+            series, x_mean, y_mean, y_sigma, _ = multi_mean_xy_data(series, x, y, method="sample")
+            expected_x_mean = np.array([1, 2, 1, 2])
+            expected_y_mean = np.array([4, 17, 150, 60])
+            expected_y_sigma = np.sqrt(np.array([4.0 / 2, 0.0 / 1, 2500.0 / 2, 66.66666667 / 3]))
+            expected_series = np.array([0, 0, 1, 1])
+            self.assertTrue(
+                np.allclose(expected_x_mean, x_mean), msg=f"{x_mean} != {expected_x_mean}"
+            )
+            self.assertTrue(
+                np.allclose(expected_y_mean, y_mean), msg=f"{y_mean} != {expected_y_mean}"
+            )
+            self.assertTrue(
+                np.allclose(expected_y_sigma, y_sigma), msg=f"{y_sigma} != {expected_y_sigma}"
+            )
+            self.assertTrue(
+                np.allclose(expected_series, series), msg=f"{series} != {expected_series}"
+            )
diff --git a/test/library/quantum_volume/qv_ideal_probabilities_qiskit_1_3.json b/test/library/quantum_volume/qv_ideal_probabilities_qiskit_1_3.json
@@ -0,0 +1 @@
+[[0.016967836206746738, 0.11989893254007651, 0.00394654461853002, 0.13589528784677357, 0.20511482048008703, 0.0816791691977386, 0.14060546401643623, 0.2958919450936116], [0.12056007843940977, 0.10070988761274678, 0.41332860589623954, 0.07543734133716322, 0.021096066850169303, 0.1601488559241172, 0.03780114546996992, 0.0709180184701846], [0.10058394660184918, 0.39126225007098714, 0.09012977139125049, 0.02982028558144569, 0.005523508253283623, 0.040983681969626276, 0.2946239196681466, 0.04707263646341052], [0.3688522014926478, 0.09580420366241688, 0.027757018918742504, 0.15826915582072928, 0.13834528025457885, 0.11281057034461814, 0.04713950685498301, 0.05102206265128345], [0.2238855389562393, 0.0177775881962427, 0.0010361793224677451, 0.49743548639570334, 0.14345035837415962, 0.010983952529157095, 0.030086371572847458, 0.07534452465318305], [0.07191730758022169, 0.08577798556935443, 0.05222185324072163, 0.011505080428938406, 0.1506083560400655, 0.07947214515779061, 0.06954659702813472, 0.4789506749547722], [0.02933798117949475, 0.0905804630987942, 0.13414073913728367, 0.3283400904287246, 0.0039327427715444745, 0.06305126971619468, 0.07960132612718543, 0.27101538754077775], [0.10361935285611489, 0.5602661574454084, 0.0033379483277632236, 0.024104300671844853, 0.11180012107386983, 0.018590174540476845, 0.06496224115302754, 0.11331970393149465], [0.28002251748562146, 0.15659108128101512, 0.06931560231414717, 0.015939512694748054, 0.20272160865971692, 0.06437155774108827, 0.17997014329975955, 0.031067976523903224], [0.2583110429786593, 0.39280733849970395, 0.01004465642965845, 0.10112365839530935, 0.04820792916847759, 0.019172100821762683, 0.07396094843817139, 0.09637232526825651], [0.04205005835070806, 0.5982838080237505, 0.24825488091343656, 0.11141125271210575, 0.0, 0.0, 0.0, 0.0], [0.21631173866223324, 0.07201585886194255, 0.19647582952426423, 0.10741584491273042, 0.054982878753641044, 0.021165794683348307, 0.2526914377956466, 0.07894061680619284], [0.04109901108305593, 0.5346418163425509, 0.0, 0.0, 0.19988603142757153, 0.22437314114682205, 0.0, 0.0], [0.1069722912636189, 0.19610594120528163, 0.13827775538043613, 0.12862292833267164, 0.05652810658633324, 0.0979666878234763, 0.15917488848657904, 0.1163514009216026], [0.1599264302659344, 0.32405634292478286, 0.050423144948197246, 0.03657193295081257, 0.13405197214337658, 0.1872187743627101, 0.0005017400591434017, 0.1072496623450432], [0.057428879095657914, 0.07553302531949552, 0.05869499440092844, 0.031696849711854186, 0.20158700775693938, 0.20118430243224272, 0.02391580078822289, 0.34995914049465865], [0.12733557958689173, 0.08478618874152216, 0.032857670388396855, 0.08627573094283553, 0.18807352626751228, 0.2365561765088683, 0.15519965863714033, 0.08891546892683337], [0.05434853562358783, 0.1282198611011262, 0.11416220587356729, 0.049568640406240184, 0.1511891111128068, 0.14032078289874864, 0.3087935419191839, 0.05339732106473909], [0.06135629616886566, 0.25774569674205117, 0.0464794921453153, 0.15917144757251409, 0.1677568850176423, 0.18787259587234334, 0.05248811617198047, 0.0671294703092877], [0.005879541314725802, 0.025021402090856428, 0.44431583322312285, 0.05198340090748109, 0.04211534913258567, 0.013297849871047806, 0.26003956333041356, 0.15734706012976746]]
diff --git a/test/library/quantum_volume/test_qv.py b/test/library/quantum_volume/test_qv.py
@@ -89,7 +89,9 @@ def test_qv_ideal_probabilities(self):
         )
         # compare to pre-calculated probabilities
         dir_name = os.path.dirname(os.path.abspath(__file__))
-        if version_is_at_least("qiskit", 1.1):
+        if version_is_at_least("qiskit", 1.3):
+            probabilities_json_file = "qv_ideal_probabilities_qiskit_1_3.json"
+        elif version_is_at_least("qiskit", 1.1):
             probabilities_json_file = "qv_ideal_probabilities_qiskit_1_1.json"
         else:
             probabilities_json_file = "qv_ideal_probabilities.json"

diff --git a/test/library/randomized_benchmarking/test_interleaved_rb.py b/test/library/randomized_benchmarking/test_interleaved_rb.py
@@ -20,6 +20,7 @@
 from qiskit.circuit import Delay, QuantumCircuit, Parameter, Gate
 from qiskit.circuit.library import SXGate, CXGate, TGate, CZGate
 from qiskit.exceptions import QiskitError
+from qiskit.providers.fake_provider import GenericBackendV2
 from qiskit.transpiler import InstructionProperties
 from qiskit_aer import AerSimulator
 from qiskit_aer.noise import NoiseModel, depolarizing_error
@@ -268,14 +269,14 @@ def test_interleaved_circuit_is_decomposed(self):
 
     def test_interleaving_cnot_gate_with_non_supported_direction(self):
         """Test if fails to interleave cx(1, 2) for backend that support only cx(2, 1)."""
-        del self.backend.target["cx"][(1, 2)]  # make support only cx(2, 1)
+        backend = GenericBackendV2(3, coupling_map=[[0, 1], [2, 1]])
 
         exp = rb.InterleavedRB(
             interleaved_element=CXGate(),
             physical_qubits=(1, 2),
             lengths=[3],
             num_samples=4,
-            backend=self.backend,
+            backend=backend,
             seed=1234,
         )
         with self.assertRaises(QiskitError):
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1 @@
		[[0.016967836206746738, 0.11989893254007651, 0.00394654461853002, 0.13589528784677357, 0.20511482048008703, 0.0816791691977386, 0.14060546401643623, 0.2958919450936116], [0.12056007843940977, 0.10070988761274678, 0.41332860589623954, 0.07543734133716322, 0.021096066850169303, 0.1601488559241172, 0.03780114546996992, 0.0709180184701846], [0.10058394660184918, 0.39126225007098714, 0.09012977139125049, 0.02982028558144569, 0.005523508253283623, 0.040983681969626276, 0.2946239196681466, 0.04707263646341052], [0.3688522014926478, 0.09580420366241688, 0.027757018918742504, 0.15826915582072928, 0.13834528025457885, 0.11281057034461814, 0.04713950685498301, 0.05102206265128345], [0.2238855389562393, 0.0177775881962427, 0.0010361793224677451, 0.49743548639570334, 0.14345035837415962, 0.010983952529157095, 0.030086371572847458, 0.07534452465318305], [0.07191730758022169, 0.08577798556935443, 0.05222185324072163, 0.011505080428938406, 0.1506083560400655, 0.07947214515779061, 0.06954659702813472, 0.4789506749547722], [0.02933798117949475, 0.0905804630987942, 0.13414073913728367, 0.3283400904287246, 0.0039327427715444745, 0.06305126971619468, 0.07960132612718543, 0.27101538754077775], [0.10361935285611489, 0.5602661574454084, 0.0033379483277632236, 0.024104300671844853, 0.11180012107386983, 0.018590174540476845, 0.06496224115302754, 0.11331970393149465], [0.28002251748562146, 0.15659108128101512, 0.06931560231414717, 0.015939512694748054, 0.20272160865971692, 0.06437155774108827, 0.17997014329975955, 0.031067976523903224], [0.2583110429786593, 0.39280733849970395, 0.01004465642965845, 0.10112365839530935, 0.04820792916847759, 0.019172100821762683, 0.07396094843817139, 0.09637232526825651], [0.04205005835070806, 0.5982838080237505, 0.24825488091343656, 0.11141125271210575, 0.0, 0.0, 0.0, 0.0], [0.21631173866223324, 0.07201585886194255, 0.19647582952426423, 0.10741584491273042, 0.054982878753641044, 0.021165794683348307, 0.2526914377956466, 0.07894061680619284], [0.04109901108305593, 0.5346418163425509, 0.0, 0.0, 0.19988603142757153, 0.22437314114682205, 0.0, 0.0], [0.1069722912636189, 0.19610594120528163, 0.13827775538043613, 0.12862292833267164, 0.05652810658633324, 0.0979666878234763, 0.15917488848657904, 0.1163514009216026], [0.1599264302659344, 0.32405634292478286, 0.050423144948197246, 0.03657193295081257, 0.13405197214337658, 0.1872187743627101, 0.0005017400591434017, 0.1072496623450432], [0.057428879095657914, 0.07553302531949552, 0.05869499440092844, 0.031696849711854186, 0.20158700775693938, 0.20118430243224272, 0.02391580078822289, 0.34995914049465865], [0.12733557958689173, 0.08478618874152216, 0.032857670388396855, 0.08627573094283553, 0.18807352626751228, 0.2365561765088683, 0.15519965863714033, 0.08891546892683337], [0.05434853562358783, 0.1282198611011262, 0.11416220587356729, 0.049568640406240184, 0.1511891111128068, 0.14032078289874864, 0.3087935419191839, 0.05339732106473909], [0.06135629616886566, 0.25774569674205117, 0.0464794921453153, 0.15917144757251409, 0.1677568850176423, 0.18787259587234334, 0.05248811617198047, 0.0671294703092877], [0.005879541314725802, 0.025021402090856428, 0.44431583322312285, 0.05198340090748109, 0.04211534913258567, 0.013297849871047806, 0.26003956333041356, 0.15734706012976746]]