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arXiv · 1901.00535

Statistical analysis of randomized benchmarking

Robin Harper·Ian Hincks·Chris Ferrie·Steven T. Flammia·Joel J. Wallman
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Abstract

Randomized benchmarking and variants thereof, which we collectively call RB+, are widely used to characterize the performance of quantum computers because they are simple, scalable, and robust to state-preparation and measurement errors. However, experimental implementations of RB+ allocate resources suboptimally and make ad-hoc assumptions that undermine the reliability of the data analysis. In this paper, we propose a simple modification of RB+ which rigorously eliminates a nuisance parameter and simplifies the experimental design. We then show that, with this modification and specific experimental choices, RB+ efficiently provides estimates of error rates with multiplicative precision. Finally, we provide a simplified rigorous method for obtaining credible regions for parameters of interest and a heuristic approximation for these intervals that performs well in currently relevant regimes.

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Robin Harper, Ian Hincks, Chris Ferrie, Steven T. Flammia, Joel J. Wallman. 2019-01-02. Statistical analysis of randomized benchmarking. https://doi.org/10.1103/physreva.99.052350

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