Measuring the capabilities of quantum computers
Quantum computers can now run interesting programs, but each processor’s capability—the set of programs that it can run successfully—is limited by hardware errors. These errors can be complicated, making it difficult to accurately predict a processor’s capability. Benchmarks can be used to measure capability directly, but current benchmarks have limited flexibility and scale poorly to many-qubit processors. We show how to construct scalable, efficiently verifiable benchmarks based on any program by using a technique that we call circuit mirroring. With it, we construct two flexible, scalable volumetric benchmarks based on randomized and periodically ordered programs. We use these benchmarks to map out the capabilities of twelve publicly available processors, and to measure the impact of program structure on each one. We find that standard error metrics are poor predictors of whether a program will run successfully on today’s hardware, and that current processors vary widely in their sensitivity to program structure.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- Grant/Contract Number:
- NA0003525
- OSTI ID:
- 1841976
- Report Number(s):
- SAND-2021-12259J; 700534
- Journal Information:
- Nature Physics, Vol. 18, Issue 1; ISSN 1745-2473
- Publisher:
- Nature Publishing Group (NPG)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
Efficient flexible characterization of quantum processors with nested error models
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journal | September 2021 |
Error-Robust Quantum Logic Optimization Using a Cloud Quantum Computer Interface
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journal | June 2021 |
| Fair Sampling Error Analysis on NISQ Devices | text | January 2021 |
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