Towards Efficient Quantum Spin System Simulations on NISQ
Norhan M Eassa, Jeffrey Cohn, et al.
APS March Meeting 2022
We introduce a Bayesian method for the estimation of single qubit errors in quantum devices, and use it to characterize these errors on two devices with 27 superconducting qubits. We self-consistently estimate up to seven parameters of each qubit's state preparation, readout, and gate errors, analyze the stability of these errors as a function of time,and demonstrate easily implemented approaches for mitigating different errors before a quantum computation experiment. On the investigated devices we find non-negligible qubit reset errors that cannot be parametrized as a diagonal mixed state, but manifest as a coherent phase of a superposition with a small contribution from the qubit's excited state, which we are able to mitigate by applying pre-rotations on the initialized qubits. Our results demonstrate that Bayesian estimation can resolve small parameters, including those pertaining to quantum gate errors, with a high relative accuracy, at a lower measurement cost as compared with standard characterization approaches.
Norhan M Eassa, Jeffrey Cohn, et al.
APS March Meeting 2022
Prakash Murali, David C. McKay, et al.
ASPLOS 2020
Jaseung Ku, Britton L Plourde, et al.
APS March Meeting 2020
Tuhin Khare, Ritajit Majumdar, et al.
QCE 2023