def benchmark_qft_qsim(from_qubits, to_qubits, results):
gc.disable()
col_qsim = "qsim"
results[col_qsim] = np.nan
for i in range(from_qubits, to_qubits + 1):
circ = qft_qsim(i)
qsim_options = {"c": circ, "i": "", "t": 1, "v": 0}
# Repeat multiple times for small number of qubits and get best time
repeat = 4 if i <= 20 else 1
qsim_time = np.nan
for r in range(repeat):
gc.collect()
start_time = time.time()
result = qsim.qsim_simulate(qsim_options)
elapsed_time = (time.time() - start_time) * 1000
qsim_time = elapsed_time if np.isnan(qsim_time) else min(
qsim_time, elapsed_time)
results[col_qsim][i] = qsim_time
gc.enable()
def test_qsim_simulate(self):
qsim_options = {
'c': '2\n0 cnot 0 1\n1 cnot 1 0\n2 cz 0 1\n',
'i': '00\n01\n10\n11',
't': 1,
'v': 0
}
self.assertSequenceEqual(
qsim.qsim_simulate(qsim_options), [(1 + 0j), 0j, 0j, 0j])
def compute_amplitudes_sweep(
self,
program: circuits.Circuit,
bitstrings: Sequence[int],
params: study.Sweepable,
qubit_order: ops.QubitOrderOrList = ops.QubitOrder.DEFAULT,
) -> Sequence[Sequence[complex]]:
"""Computes the desired amplitudes using qsim.
The initial state is assumed to be the all zeros state.
Args:
program: The circuit to simulate.
bitstrings: The bitstrings whose amplitudes are desired, input as an
string array where each string is formed from measured qubit values
according to `qubit_order` from most to least significant qubit,
i.e. in big-endian ordering.
param_resolver: Parameters to run with the program.
qubit_order: Determines the canonical ordering of the qubits. This is
often used in specifying the initial state, i.e. the ordering of the
computational basis states.
Returns:
List of amplitudes.
"""
if not isinstance(program, qsimc.QSimCircuit):
program = qsimc.QSimCircuit(program, device=program.device)
n_qubits = len(program.all_qubits())
# qsim numbers qubits in reverse order from cirq
bitstrings = [
format(bitstring, 'b').zfill(n_qubits)[::-1]
for bitstring in bitstrings
]
options = {'i': '\n'.join(bitstrings)}
options.update(self.qsim_options)
param_resolvers = study.to_resolvers(params)
trials_results = []
for prs in param_resolvers:
solved_circuit = protocols.resolve_parameters(program, prs)
options['c'] = solved_circuit.translate_cirq_to_qsim(qubit_order)
options['s'] = self.get_seed()
amplitudes = qsim.qsim_simulate(options)
trials_results.append(amplitudes)
return trials_results
