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Trapped Ion Quantum Computing

A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors

arXiv

Authors: Muqing Zheng, Ang Li, Tamás Terlaky, Xiu Yang

Year

2020

Paper ID

19857

Status

Preprint

Abstract Read

~2 min

Abstract Words

115

Citations

N/A

Abstract

Various noise models have been developed in quantum computing study to describe the propagation and effect of the noise which is caused by imperfect implementation of hardware. Identifying parameters such as gate and readout error rates are critical to these models. We use a Bayesian inference approach to identity 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 such experiments.

Why This Paper Matters

This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
It adds a 2020 reference point for readers tracking recent quantum research.
Various noise models have been developed in quantum computing study to describe the propagation and effect of the noise which is caused by imperfect implementation of hardware.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2010.09188 [2] arXiv https://arxiv.org/abs/2010.09188 [3] Publisher https://arxiv.org/abs/2010.09188

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