Mitiq: A software package for error mitigation on noisy quantum computers
1Unitary Fund
2Michigan State University, East Lansing, MI
3AWS Center for Quantum Computing, Pasadena, CA 91125, USA
4Hamburg University of Applied Sciences, Hamburg, Germany
5Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
6Institute for Quantum Computing, University of Waterloo, Waterloo, ON, N2L 3G1, Canada
7Instituto de Física Teórica, UAM/CSIC, Universidad Autónoma de Madrid, Madrid, Spain
8Stanford University, Palo Alto, CA
9Independent researcher
10Southern Illinois University, Carbondale, IL
11Institut quantique, Université de Sherbrooke, Sherbrooke, QC, J1K 2R1, Canada
12Goldman, Sachs & Co, New York, NY
| Published: | 2022-08-11, volume 6, page 774 |
| Eprint: | arXiv:2009.04417v4 |
| Doi: | https://doi.org/10.22331/q-2022-08-11-774 |
| Citation: | Quantum 6, 774 (2022). |
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Abstract
We introduce Mitiq, a Python package for error mitigation on noisy quantum computers. Error mitigation techniques can reduce the impact of noise on near-term quantum computers with minimal overhead in quantum resources by relying on a mixture of quantum sampling and classical post-processing techniques. Mitiq is an extensible toolkit of different error mitigation methods, including zero-noise extrapolation, probabilistic error cancellation, and Clifford data regression. The library is designed to be compatible with generic backends and interfaces with different quantum software frameworks. We describe Mitiq using code snippets to demonstrate usage and discuss features and contribution guidelines. We present several examples demonstrating error mitigation on IBM and Rigetti superconducting quantum processors as well as on noisy simulators.
Featured image: Mitiq project logo
Popular summary
Current quantum computers are noisy due to interactions with the environment, imperfect gate applications, state preparation and measurement errors, etc. Error mitigation seeks to reduce these effects with minimal overhead in quantum resources by relying on a mixture of quantum sampling and classical post-processing techniques.
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