{"title":"自旋维格纳函数核的噪声裁剪构造","authors":"Michael Hanks, Soovin Lee, M.S. Kim","doi":"10.1002/apxr.202300124","DOIUrl":null,"url":null,"abstract":"<p>The effective use of noisy intermediate-scale quantum devices requires error mitigation to improve the accuracy of sampled measurement distributions. The more accurately the effects of noise on these distributions can be modeled, the more closely error mitigation will be able to approach theoretical bounds. The characterization of noisy quantum channels and the inference of their effects on general observables are challenging problems, but in many cases a change in representation can greatly simplify the analysis. Here, spin Wigner functions for multiqudit systems are investigated. This study generalizes previous kernel constructions, capturing the effects of several probabilistic unitary noise models in few parameters.</p>","PeriodicalId":100035,"journal":{"name":"Advanced Physics Research","volume":"3 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/apxr.202300124","citationCount":"0","resultStr":"{\"title\":\"Noise-Tailored Constructions for Spin Wigner Function Kernels\",\"authors\":\"Michael Hanks, Soovin Lee, M.S. Kim\",\"doi\":\"10.1002/apxr.202300124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The effective use of noisy intermediate-scale quantum devices requires error mitigation to improve the accuracy of sampled measurement distributions. The more accurately the effects of noise on these distributions can be modeled, the more closely error mitigation will be able to approach theoretical bounds. The characterization of noisy quantum channels and the inference of their effects on general observables are challenging problems, but in many cases a change in representation can greatly simplify the analysis. Here, spin Wigner functions for multiqudit systems are investigated. This study generalizes previous kernel constructions, capturing the effects of several probabilistic unitary noise models in few parameters.</p>\",\"PeriodicalId\":100035,\"journal\":{\"name\":\"Advanced Physics Research\",\"volume\":\"3 6\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/apxr.202300124\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Physics Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/apxr.202300124\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Physics Research","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/apxr.202300124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Noise-Tailored Constructions for Spin Wigner Function Kernels
The effective use of noisy intermediate-scale quantum devices requires error mitigation to improve the accuracy of sampled measurement distributions. The more accurately the effects of noise on these distributions can be modeled, the more closely error mitigation will be able to approach theoretical bounds. The characterization of noisy quantum channels and the inference of their effects on general observables are challenging problems, but in many cases a change in representation can greatly simplify the analysis. Here, spin Wigner functions for multiqudit systems are investigated. This study generalizes previous kernel constructions, capturing the effects of several probabilistic unitary noise models in few parameters.