Classical shadows based on locally-entangled measurements
Author:
Affiliation:
1. Department of Physics, The University of Texas at Austin, Austin, TX 78712, USA
2. Department of Physics, Stanford University, Stanford, CA 94305, USA
Abstract
Funder
Gordon and Betty Moore Foundation
Publisher
Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften
Link
https://quantum-journal.org/papers/q-2024-03-21-1293/pdf/
Reference60 articles.
1. Hsin-Yuan Huang, Richard Kueng, and John Preskill. ``Predicting many properties of a quantum system from very few measurements''. Nature Physics 16, 1050–1057 (2020).
2. Andreas Elben, Steven T. Flammia, Hsin-Yuan Huang, Richard Kueng, John Preskill, Benoit Vermersch, and Peter Zoller. ``The randomized measurement toolbox''. Nature Reviews Physics 5, 9–24 (2023).
3. Charles Hadfield, Sergey Bravyi, Rudy Raymond, and Antonio Mezzacapo. ``Measurements of Quantum Hamiltonians with Locally-Biased Classical Shadows'' (2020). arXiv:2006.15788.
4. Senrui Chen, Wenjun Yu, Pei Zeng, and Steven T. Flammia. ``Robust Shadow Estimation''. PRX Quantum 2, 030348 (2021).
5. Atithi Acharya, Siddhartha Saha, and Anirvan M. Sengupta. ``Shadow tomography based on informationally complete positive operator-valued measure''. Physical Review A 104, 052418 (2021).
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Many-Body Entropies and Entanglement from Polynomially Many Local Measurements;Physical Review X;2024-08-26
2. Efficient Local Classical Shadow Tomography with Number Conservation;Physical Review Letters;2024-08-07
3. Error-mitigated fermionic classical shadows on noisy quantum devices;npj Quantum Information;2024-04-16
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3