A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors
Abstract
Various noise models have been developed in quantum computing study to describe the propagation and effect of the noise that is caused by imperfect implementation of hardware. Identifying parameters such as gate and readout error rates is critical to these models. We use a Bayesian inference approach to identify posterior distributions of these parameters such that they can be characterized more elaborately. By characterizing the device errors in this way, we can further improve the accuracy of quantum error mitigation. Experiments conducted on IBM’s quantum computing devices suggest that our approach provides better error mitigation performance than existing techniques used by the vendor. Also, our approach outperforms the standard Bayesian inference method in some scenarios.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Feb 24, 2023
- Source ID
- 10.1145/3563397
Entities
People
- Ang Li
- Muqing Zheng
- Tamás Terlaky
- Xiu Yang
Organizations
- Defense Advanced Research Projects Agency
- Lehigh University
- National Energy Research Scientific Computing Center
- Office of Science
- Pacific Northwest National Laboratory
- United States Department of Energy