Randomised Benchmarking: Difference between revisions
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==Functionality Description== | ==Functionality Description== | ||
Randomized benchmarking | Randomized benchmarking refers to a collection of methods that aim to reliably estimating the magnitude of an average error of a quantum gate set in a robust fashion against state preparation and measurement error. One key [[figure of merit]] here is average gate fidelity. It achieves this goal by applying sequences of feasible quantum gates of varying length, so that small errors are amplified leading to reliable estimation. | ||
==Protocols== | ==Protocols== | ||
Revision as of 12:24, 20 November 2019
Functionality Description
Randomized benchmarking refers to a collection of methods that aim to reliably estimating the magnitude of an average error of a quantum gate set in a robust fashion against state preparation and measurement error. One key figure of merit here is average gate fidelity. It achieves this goal by applying sequences of feasible quantum gates of varying length, so that small errors are amplified leading to reliable estimation.
Protocols
Properties
- The noise model is assumed to be IID.
- This method is insensitive to the SPAM errors
- The figure of merit is average error rate, average fidelity of a noise quantum circuit.
- This method is a certification technique which has lower sample and resource complexity than Tomography
Related Papers
- E.Knill et al (2007) arXiv:0707.0963: gate and time-independent noise model
- E. Mageson et al (2011) arXiv:1009.3639: multi-parameter model
- Magesan et al. PRL (2012): Interleaved Randomized Benchmarking
- Harper et al (2016) arXiv:1608.02943v2: Interleaved Randomised Benchmarking to estimate fidelity of T gates
- Wallman, Granade, Harper, F., NJP 2015: Purity benchmarking
*contributed by Rhea Parekh