Benchmarks

BaseBenchmark(name, qubits[, save_path])	Abstract base class for quantum computing benchmarks.
BenchmarkCollection(benchmarks[, save_path])	A collection of BaseBenchmark instances.
T1([qubit_index, num_idle_gates_per_circ, ...])	Benchmark class for estimating the T1 relaxation time of a qubit using idle gate sequences.
T2([qubit_index, method, ...])	Benchmark class for estimating the T2 coherence time of a qubit.
IdleQubitOscillationFrequency(dt, t_max[, ...])	Implementation of the idle qubit oscillation frequency metric.
CliffordRB(m_list[, circs_per_m, qubits, ...])	Implements Clifford Randomised Benchmarking Average Gate Error Metric.
CycleBenchmarking(g_layer, repetitions_list)	Benchmark class for estimating composite process fidelity using cycle benchmarking.
OverUnderRotationAngle([qubits, delta_m, ...])	Benchmark to estimate coherent over-/under-rotation on one qubit.
GST(gst_experiment_design[, save_path, ...])	Run Gate Set Tomography (GST) with pyGSTi in a minimal QCMet-friendly way.
MirroredCircuits(qubits, num_circuits[, m, ...])	Implementation of the mirrored circuits average polarization metric.
QuantumVolumeFixedQubits([trials, qubits, ...])	Implementation of the Quantum Volume Metric.
UpperBoundOnVD(target_circuit[, mu, eta, ...])	Implementation of the upper bound on the variation distance (VD) metric.
QFT(qubits[, save_path, seed])	Implementation of the Quantum Fourier Transform (QFT) metric.
QScoreSingleInstance(qubits, depth[, ...])	Implementation of the QScore (MaxCut-based) metric for a fixed number of qubits.
HamiltonianSimulation(simulation_name, qubits)	Benchmark class for simulating quantum dynamics of a Hamiltonian with Trotter evolution.
Simulation1DFermiHubbard(qubits[, U, t, ...])	Simulates the dynamics of a 1D Hubbard model using Trotter decomposition.
VQE1DFermiHubbard(qubits[, U, t, ...])	Variational Quantum Eigensolver implementation for the 1D Fermi-Hubbard model.
VQE(VQEName, qubits[, hamiltonian, ansatz, ...])	Variational Quantum Eigensolver (VQE) benchmark class.