A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors

A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors
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用于表征和减轻门和测量误差的贝叶斯方法

DOI:
10.1145/3563397
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发表时间:
2023
期刊:
ACM Transactions on Quantum Computing
影响因子:
--
通讯作者:
Yang, Xiu
Yang, Xiu
中科院分区:
--
文献类型:
--
作者:
Zheng, Muqing;Li, Ang;Terlaky, Tamás;Yang, Xiu

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在量子计算研究中,已经发展了各种噪声模型来描述由于硬件实现不完善而引起的噪声的传播和影响。识别门和读出错误率等参数对这些模型至关重要。我们使用贝叶斯推断方法来识别这些参数的后验分布,以便能够更精细地刻画它们。通过这种方法对器件误差进行表征,可以进一步提高量子误差抑制的精度。在IBM的量子计算设备上进行的实验表明,我们的方法提供了比供应商使用的现有技术更好的错误缓解性能。此外,在某些情况下,我们的方法要优于标准的贝叶斯推理方法。
Various noise models have been developed in quantum computing study to describe the propagation and effect of the noise that is caused by imperfect implementation of hardware. Identifying parameters such as gate and readout error rates is critical to these models. We use a Bayesian inference approach to identify 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 some scenarios.
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