qiskit-aer/test/benchmark/output_25q.py

87 lines
2.5 KiB
Python

# This code is part of Qiskit.
#
# (C) Copyright IBM 2018, 2019, 2020.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""
Output Benchmarking with 25 qubits
"""
from benchmark.simulator_benchmark import SimulatorBenchmarkSuite
from benchmark.output import OutputSimulatorBenchmarkSuite
DEFAULT_APPS = {
# 'fourier_checking',
# 'graph_state',
# 'hidden_linear_function',
# 'iqp',
"quantum_volume": 1,
# 'phase_estimation'
}
DEFAULT_QUBITS = [25]
DEFAULT_RUNTIME = [
SimulatorBenchmarkSuite.RUNTIME_STATEVECTOR_CPU,
SimulatorBenchmarkSuite.RUNTIME_STATEVECTOR_GPU,
# SimulatorBenchmarkSuite.RUNTIME_MPS_CPU,
]
DEFAULT_MEASUREMENT_COUNTS = [1, 10, 100, 1000, 10000]
DEFAULT_NOISE_MODELS = [SimulatorBenchmarkSuite.NOISE_IDEAL]
class Sampling(OutputSimulatorBenchmarkSuite):
def __init__(
self,
apps=DEFAULT_APPS,
qubits=DEFAULT_QUBITS,
runtime_names=DEFAULT_RUNTIME,
measures=[SimulatorBenchmarkSuite.MEASUREMENT_SAMPLING],
measure_counts=DEFAULT_MEASUREMENT_COUNTS,
noise_model_names=DEFAULT_NOISE_MODELS,
):
super().__init__(
"sampling",
apps,
qubits=qubits,
runtime_names=runtime_names,
measures=measures,
measure_counts=measure_counts,
noise_model_names=noise_model_names,
)
self.__name__ = "sampling"
class ExpVal(OutputSimulatorBenchmarkSuite):
def __init__(
self,
apps=DEFAULT_APPS,
qubits=DEFAULT_QUBITS,
runtime_names=DEFAULT_RUNTIME,
measures=[SimulatorBenchmarkSuite.MEASUREMENT_EXPVAL],
measure_counts=DEFAULT_MEASUREMENT_COUNTS,
noise_model_names=DEFAULT_NOISE_MODELS,
):
super().__init__(
"expval",
apps,
qubits=qubits,
runtime_names=runtime_names,
measures=measures,
measure_counts=measure_counts,
noise_model_names=noise_model_names,
)
self.__name__ = "expval"
if __name__ == "__main__":
Sampling().run_manual()
ExpVal().run_manual()