表征和减轻门和测量误差的贝叶斯方法

Muqing Zheng, Ang Li, T. Terlaky, Xiu Yang
{"title":"表征和减轻门和测量误差的贝叶斯方法","authors":"Muqing Zheng, Ang Li, T. Terlaky, Xiu Yang","doi":"10.1145/3563397","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":365166,"journal":{"name":"ACM Transactions on Quantum Computing","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors\",\"authors\":\"Muqing Zheng, Ang Li, T. Terlaky, Xiu Yang\",\"doi\":\"10.1145/3563397\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":365166,\"journal\":{\"name\":\"ACM Transactions on Quantum Computing\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Quantum Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3563397\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Quantum Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3563397","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

摘要

在量子计算研究中,已经发展了各种各样的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。识别诸如门和读出错误率之类的参数对这些模型至关重要。我们使用贝叶斯推理方法来识别这些参数的后验分布,以便它们可以更详细地表征。通过这种方式表征器件误差,我们可以进一步提高量子误差缓解的准确性。在IBM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,我们的方法在某些情况下优于标准贝叶斯推理方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Revisiting the Mapping of Quantum Circuits: Entering the Multi-Core Era An optimal linear-combination-of-unitaries-based quantum linear system solver Efficient Syndrome Decoder for Heavy Hexagonal QECC via Machine Learning Improving the Efficiency of Quantum Circuits for Information Set Decoding Quantum Bilinear Interpolation Algorithms Based on Geometric Centers
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1