Qiskit Experiments

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0.13.0 verified Fri May 01 auth: no python

A library for building, running, and analyzing quantum computing experiments on IBM Qiskit. Current version 0.13.0, released quarterly. Provides experiment classes, analysis modules, and database storage. Requires qiskit-terra and qiskit-ibm-runtime.

pip install qiskit-experiments
error ModuleNotFoundError: No module named 'qiskit_experiments'
cause qiskit-experiments not installed or installed in a different environment.
fix
Run pip install qiskit-experiments in your current Python environment.
error AttributeError: module 'qiskit_experiments' has no attribute 'Experiment'
cause Importing Experiment from the wrong location (top-level instead of framework).
fix
Use from qiskit_experiments.framework import Experiment
error TypeError: 'NoneType' object is not subscriptable when accessing analysis_results()
cause ExperimentData not blocked for results before reading.
fix
Call .block_for_results() on the ExperimentData object before accessing analysis_results().
breaking Database storage (DbExperimentDataV2) is deprecated since 0.12 and removed in 0.13. Use memory-based ExperimentData instead.
fix Remove any usage of DbExperimentDataV2. For persistent storage, manually serialize ExperimentData to JSON or use the new database service (qiskit_experiments.database_service), which is still experimental.
deprecated The `from qiskit_experiments.data_processing` module is deprecated since 0.10. Use `data_processing` from `qiskit_experiments.framework` instead.
fix Change imports: from qiskit_experiments.framework.data_processing import DataProcessor
gotcha When running on real hardware, you must pass a backend obtained from qiskit_ibm_runtime, not qiskit.providers.ibmq.
fix Use `from qiskit_ibm_runtime import QiskitRuntimeService; service = QiskitRuntimeService(); backend = service.backend('ibm_qasm_simulator')`.

Run a simple randomized benchmarking experiment on a fake backend, then print analysis results.

from qiskit.providers.fake_provider import FakePerth
from qiskit_experiments.library import RandomizedBenchmarking
from qiskit_experiments.framework import ExperimentData

backend = FakePerth()
exp = RandomizedBenchmarking(qubits=(0,), lengths=[1, 10, 20], num_samples=10)
exp_data = exp.run(backend, shots=1024).block_for_results()
print(exp_data.analysis_results())