Replace qiskit.providers.basicaer test usage with qiskit-aer

qiskit.providers.basicaer was removed in Qiskit 1.0. See
Qiskit/qiskit#11422

test/curve_analysis/test_curve_fitting.py

@@ -15,7 +15,7 @@
 import numpy as np
 
 from qiskit import QuantumCircuit, transpile
-from qiskit.providers.basicaer import QasmSimulatorPy
+from qiskit_aer import AerSimulator
 from qiskit_experiments.curve_analysis import process_curve_data
 from qiskit_experiments.curve_analysis.utils import (
     level2_probability,
@@ -36,7 +36,7 @@ def simulate_experiment_data(self, thetas, shots=1024):
             qc.measure_all()
             circuits.append(qc)
 
-        sim = QasmSimulatorPy()
+        sim = AerSimulator()
         circuits = transpile(circuits, sim)
         job = sim.run(circuits, shots=shots, seed_simulator=10)
         result = job.result()

test/library/calibration/test_rabi.py

@@ -18,8 +18,9 @@
 from qiskit import QuantumCircuit, pulse, transpile
 from qiskit.exceptions import QiskitError
 from qiskit.circuit import Parameter
-from qiskit.providers.basicaer import QasmSimulatorPy
 from qiskit.qobj.utils import MeasLevel
+from qiskit.providers.basic_provider import BasicSimulator
+from qiskit_aer import AerSimulator
 
 from qiskit_experiments.framework import ExperimentData, ParallelExperiment
 from qiskit_experiments.library import Rabi, EFRabi
@@ -223,7 +224,7 @@ def simulate_experiment_data(self, thetas, amplitudes, shots=1024):
             qc.measure_all()
             circuits.append(qc)
 
-        sim = QasmSimulatorPy()
+        sim = AerSimulator()
         circuits = transpile(circuits, sim)
         job = sim.run(circuits, shots=shots, seed_simulator=10)
         result = job.result()
@@ -272,15 +273,18 @@ def test_bad_analysis(self):
         """Test the Rabi analysis."""
         experiment_data = ExperimentData()
 
-        thetas = np.linspace(0.0, np.pi / 4, 31)
+        # Change rotation angle with square root of amplitude so that
+        # population versus amplitude will not be sinusoidal and the fit will
+        # be bad.
+        thetas = np.sqrt(np.linspace(0.0, 4 * np.pi**2, 31))
         amplitudes = np.linspace(0.0, 0.95, 31)
 
         experiment_data.add_data(self.simulate_experiment_data(thetas, amplitudes, shots=200))
 
         data_processor = DataProcessor("counts", [Probability(outcome="1")])
 
         experiment_data = OscillationAnalysis().run(
-            experiment_data, data_processor=data_processor, plot=False
+            experiment_data, data_processor=data_processor, #plot=False
         )
         result = experiment_data.analysis_results()