def test_benchmark_2q_xeb_fidelities_parallel():
circuits = rqcg.generate_library_of_2q_circuits(
n_library_circuits=5,
two_qubit_gate=cirq.ISWAP**0.5,
max_cycle_depth=4)
cycle_depths = [2, 3, 4]
graph = _gridqubits_to_graph_device(cirq.GridQubit.rect(2, 2))
combs = rqcg.get_random_combinations_for_device(
n_library_circuits=len(circuits),
n_combinations=2,
device_graph=graph,
random_state=10)
sampled_df = sample_2q_xeb_circuits(
sampler=cirq.Simulator(),
circuits=circuits,
cycle_depths=cycle_depths,
combinations_by_layer=combs,
)
fid_df = benchmark_2q_xeb_fidelities(sampled_df, circuits, cycle_depths)
n_pairs = sum(len(c.pairs) for c in combs)
assert len(fid_df) == len(cycle_depths) * n_pairs
fit_df = fit_exponential_decays(fid_df)
for _, row in fit_df.iterrows():
assert list(row['cycle_depths']) == list(cycle_depths)
assert len(row['fidelities']) == len(cycle_depths)
def test_benchmark_2q_xeb_fidelities():
q0, q1 = cirq.LineQubit.range(2)
circuits = [
rqcg.random_rotations_between_two_qubit_circuit(
q0,
q1,
depth=50,
two_qubit_op_factory=lambda a, b, _: SQRT_ISWAP(a, b),
seed=52) for _ in range(2)
]
cycle_depths = np.arange(3, 50, 9)
sampled_df = sample_2q_xeb_circuits(sampler=cirq.Simulator(seed=53),
circuits=circuits,
cycle_depths=cycle_depths)
fid_df = benchmark_2q_xeb_fidelities(sampled_df, circuits, cycle_depths)
assert len(fid_df) == len(cycle_depths)
for _, row in fid_df.iterrows():
assert row['cycle_depth'] in cycle_depths
assert row['fidelity'] > 0.98
fit_df = fit_exponential_decays(fid_df)
for _, row in fit_df.iterrows():
assert list(row['cycle_depths']) == list(cycle_depths)
assert len(row['fidelities']) == len(cycle_depths)
def test_benchmark_2q_xeb_fidelities(circuits_cycle_depths_sampled_df, pass_cycle_depths):
circuits, cycle_depths, sampled_df = circuits_cycle_depths_sampled_df
if pass_cycle_depths:
fid_df = benchmark_2q_xeb_fidelities(sampled_df, circuits, cycle_depths)
else:
fid_df = benchmark_2q_xeb_fidelities(sampled_df, circuits)
assert len(fid_df) == len(cycle_depths)
assert sorted(fid_df['cycle_depth'].unique()) == cycle_depths.tolist()
assert np.all(fid_df['fidelity'] > 0.98)
fit_df = fit_exponential_decays(fid_df)
for _, row in fit_df.iterrows():
assert list(row['cycle_depths']) == list(cycle_depths)
assert len(row['fidelities']) == len(cycle_depths)
