Characterization and Benchmarking of Quantum Computers
ORAL
Abstract
Effective methods for characterizing noise in quantum computing devices are essential for improving hardware and programming quantum circuits. Existing approaches vary in information obtained as well as amount of quantum and classical resources needed—generally, more information requires more resources. We benchmark the characterization methods of gate set tomography, Pauli channel noise reconstruction, and empirical direct characterization (EDC) by comparing their estimated models that describe noisy quantum circuit performance on a 27-qubit superconducting transmon device. We evaluate these models by comparing the accuracy of noisy circuit simulations with corresponding experimental observations. We find that agreement of noise model to experiment does not correlate with information gained by characterization and the underlying circuit strongly influences the best choice of characterization approach. The EDC method scales best of the methods we tested and produced the most accurate characterizations across our benchmarks.
*This research is supported by the Department of Energy Office of Science Early Career Research Program and used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.
–
Publication: Dahlhauser, Megan L., "Characterization and Benchmarking of Quantum Computers. " PhD diss., University of Tennessee, 2021.
https://trace.tennessee.edu/utk_graddiss/6659
Presenters
-
Megan L Dahlhauser
- Sandia National Laboratories