分析具有信息含量的变分量子景观

IF 6.6 1区 物理与天体物理 Q1 PHYSICS, APPLIED npj Quantum Information Pub Date : 2024-02-29 DOI:10.1038/s41534-024-00819-8
Adrián Pérez-Salinas, Hao Wang, Xavier Bonet-Monroig
{"title":"分析具有信息含量的变分量子景观","authors":"Adrián Pérez-Salinas, Hao Wang, Xavier Bonet-Monroig","doi":"10.1038/s41534-024-00819-8","DOIUrl":null,"url":null,"abstract":"<p>The parameters of the quantum circuit in a variational quantum algorithm induce a landscape that contains the relevant information regarding its optimization hardness. In this work, we investigate such landscapes through the lens of information content, a measure of the variability between points in parameter space. Our major contribution connects the information content to the average norm of the gradient, for which we provide robust analytical bounds on its estimators. This result holds for any (classical or quantum) variational landscape. We validate the analytical understating by numerically studying the scaling of the gradient in an instance of the barren plateau problem. In such instance, we are able to estimate the scaling pre-factors in the gradient. Our work provides a way to analyze variational quantum algorithms in a data-driven fashion well-suited for near-term quantum computers.</p>","PeriodicalId":19212,"journal":{"name":"npj Quantum Information","volume":"50 1","pages":""},"PeriodicalIF":6.6000,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analyzing variational quantum landscapes with information content\",\"authors\":\"Adrián Pérez-Salinas, Hao Wang, Xavier Bonet-Monroig\",\"doi\":\"10.1038/s41534-024-00819-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The parameters of the quantum circuit in a variational quantum algorithm induce a landscape that contains the relevant information regarding its optimization hardness. In this work, we investigate such landscapes through the lens of information content, a measure of the variability between points in parameter space. Our major contribution connects the information content to the average norm of the gradient, for which we provide robust analytical bounds on its estimators. This result holds for any (classical or quantum) variational landscape. We validate the analytical understating by numerically studying the scaling of the gradient in an instance of the barren plateau problem. In such instance, we are able to estimate the scaling pre-factors in the gradient. Our work provides a way to analyze variational quantum algorithms in a data-driven fashion well-suited for near-term quantum computers.</p>\",\"PeriodicalId\":19212,\"journal\":{\"name\":\"npj Quantum Information\",\"volume\":\"50 1\",\"pages\":\"\"},\"PeriodicalIF\":6.6000,\"publicationDate\":\"2024-02-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"npj Quantum Information\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1038/s41534-024-00819-8\",\"RegionNum\":1,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHYSICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Quantum Information","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1038/s41534-024-00819-8","RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHYSICS, APPLIED","Score":null,"Total":0}
引用次数: 0

摘要

变分量子算法中的量子电路参数会诱发一种景观,其中包含与其优化硬度相关的信息。在这项工作中,我们从信息含量的角度研究了这种景观,信息含量是参数空间中各点之间可变性的度量。我们的主要贡献是将信息含量与梯度的平均规范联系起来,并为其估计值提供了稳健的分析约束。这一结果适用于任何(经典或量子)变分景观。我们通过数值研究贫瘠高原问题实例中的梯度缩放,验证了分析性估计。在这种情况下,我们能够估算出梯度的缩放预因子。我们的工作提供了一种以数据驱动的方式分析变分量子算法的方法,非常适合近期量子计算机。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
Analyzing variational quantum landscapes with information content

The parameters of the quantum circuit in a variational quantum algorithm induce a landscape that contains the relevant information regarding its optimization hardness. In this work, we investigate such landscapes through the lens of information content, a measure of the variability between points in parameter space. Our major contribution connects the information content to the average norm of the gradient, for which we provide robust analytical bounds on its estimators. This result holds for any (classical or quantum) variational landscape. We validate the analytical understating by numerically studying the scaling of the gradient in an instance of the barren plateau problem. In such instance, we are able to estimate the scaling pre-factors in the gradient. Our work provides a way to analyze variational quantum algorithms in a data-driven fashion well-suited for near-term quantum computers.

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
npj Quantum Information
npj Quantum Information Computer Science-Computer Science (miscellaneous)
CiteScore
13.70
自引率
3.90%
发文量
130
审稿时长
29 weeks
期刊介绍: The scope of npj Quantum Information spans across all relevant disciplines, fields, approaches and levels and so considers outstanding work ranging from fundamental research to applications and technologies.
期刊最新文献
Characterizing coherent errors using matrix-element amplification Many-body entanglement via ‘which-path’ information Hardware-tailored diagonalization circuits Optical and spin coherence of Er spin qubits in epitaxial cerium dioxide on silicon Local testability of distance-balanced quantum codes
×
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