A Methodology to Select and Adjust Quantum Noise Models Through Emulators: Benchmarking Against Real Backends

Abstract Currently, access to quantum processors is costly in terms of time, and power.There are quantum simulators and emulators on the market that offer alternativesfor evaluating the behavior of a real quantum processor. However, these emulationenvironments present accuracy deviations from real devices, mainly becauseof difficult-to-model error sources. In this study, a methodology is proposed thatallows the selection of noise models and adjustment of their parameters, consideringthe nature of the backends (technology, topology, vendor, model, etc.).The proposed methodology is illustrated using a small superconducting examplebased on the ibm perth backend (seven qubits) and a comparison between thequantum emulators Qaptiva and Qiskit, where six different noise models areapplied, achieving a fidelity deviation of 0.686% at best with respect to the real device.