Note

This is the documentation for the current state of the development branch of Qiskit Experiments. The documentation or APIs here can change prior to being released.

QuantumVolume¶

class QuantumVolume(physical_qubits, backend=None, trials=100, seed=None, simulation_backend=None)[source]¶

An experiment to measure the largest random square circuit that can be run on a processor.

Overview

Quantum Volume (QV) is a single-number metric that can be measured using a concrete protocol on near-term quantum computers of modest size. The QV method quantifies the largest random circuit of equal width and depth that the computer successfully implements. Quantum computing systems with high-fidelity operations, high connectivity, large calibrated gate sets, and circuit rewriting toolchains are expected to have higher quantum volumes.

The Quantum Volume is determined by the largest circuit depth $d_{m a x}$ , and equals to $2^{d_{m a x}}$ . See Qiskit Textbook for an explanation on the QV protocol.

In the QV experiment we generate QuantumVolume circuits on $d$ qubits, which contain $d$ layers, where each layer consists of random 2-qubit unitary gates from $S U (4)$ , followed by a random permutation on the $d$ qubits. Then these circuits run on the quantum backend and on an ideal simulator (either AerSimulator or Statevector).

A depth $d$ QV circuit is successful if it has ‘mean heavy-output probability’ > 2/3 with confidence level > 0.977 (corresponding to z_value = 2), and at least 100 trials have been ran.

See QuantumVolumeAnalysis documentation for additional information on QV experiment analysis.

References

[1] Andrew W. Cross, Lev S. Bishop, Sarah Sheldon, Paul D. Nation, Jay M. Gambetta, Validating quantum computers using randomized model circuits, Phys. Rev. A 100, 032328 (2019), doi: 10.1103/PhysRevA.100.032328 (open)

[2] Petar Jurcevic, Ali Javadi-Abhari, Lev S. Bishop, Isaac Lauer, Daniela F. Bogorin, Markus Brink, Lauren Capelluto, Oktay Günlük, Toshinari Itoko, Naoki Kanazawa, Abhinav Kandala, George A. Keefe, Kevin Krsulich, William Landers, Eric P. Lewandowski, Douglas T. McClure, Giacomo Nannicini, Adinath Narasgond, Hasan M. Nayfeh, Emily Pritchett, Mary Beth Rothwell, Srikanth Srinivasan, Neereja Sundaresan, Cindy Wang, Ken X. Wei, Christopher J. Wood, Jeng-Bang Yau, Eric J. Zhang, Oliver E. Dial, Jerry M. Chow, Jay M. Gambetta, Demonstration of quantum volume 64 on a superconducting quantum computing system, Quantum Sci. Technol. 6 025020 (2021), doi: 10.1088/2058-9565/abe519 (open)

Analysis class reference

QuantumVolumeAnalysis

Experiment options

These options can be set by the set_experiment_options() method.

Options

Defined in the class QuantumVolume:
- trials (int)
  
  Default value: 100
  
  Optional, number of times to generate new Quantum Volume circuits and calculate their heavy output.
- seed (None or int or SeedSequence or BitGenerator or Generator)
  
  Default value: None
  
  A seed used to initialize numpy.random.default_rng when generating circuits. The default_rng will be initialized with this seed value everytime circuits() is called.
Defined in the class BaseExperiment:
- max_circuits (Optional[int])
  
  Default value: None
  
  The maximum number of circuits per job when running an experiment on a backend.

Initialization

Initialize a quantum volume experiment.

Parameters:

physical_qubits (Sequence[int]) – list of physical qubits for the experiment.
backend (Optional[Backend]) – Optional, the backend to run the experiment on.
trials (Optional[int]) – The number of trials to run the quantum volume circuit.
seed (Union[int, SeedSequence, BitGenerator, Generator, None]) – Optional, seed used to initialize numpy.random.default_rng when generating circuits. The default_rng will be initialized with this seed value everytime circuits() is called.
simulation_backend (Optional[Backend]) – The simulator backend to use to generate the expected results. the simulator must have a ‘save_probabilities’ method. If None AerSimulator simulator will be used (in case AerSimulator is not installed qiskit.quantum_info.Statevector will be used).

Attributes

`QuantumVolume.analysis`	Return the analysis instance for the experiment
`QuantumVolume.backend`	Return the backend for the experiment
`QuantumVolume.experiment_options`	Return the options for the experiment.
`QuantumVolume.experiment_type`	Return experiment type.
`QuantumVolume.num_qubits`	Return the number of qubits for the experiment.
`QuantumVolume.physical_qubits`	Return the device qubits for the experiment.
`QuantumVolume.run_options`	Return options values for the experiment `run()` method.
`QuantumVolume.transpile_options`	Return the transpiler options for the `run()` method.

Methods

`QuantumVolume.circuits`()	Return a list of Quantum Volume circuits.
`QuantumVolume.config`()	Return the config dataclass for this experiment
`QuantumVolume.copy`()	Return a copy of the experiment
`QuantumVolume.from_config`(config)	Initialize an experiment from experiment config
`QuantumVolume.run`([backend, analysis, timeout])	Run an experiment and perform analysis.
`QuantumVolume.set_experiment_options`(**fields)	Set the experiment options.
`QuantumVolume.set_run_options`(**fields)	Set options values for the experiment `run()` method.
`QuantumVolume.set_transpile_options`(**fields)	Set the transpiler options for `run()` method.