Preparing random states and benchmarking with many-body quantum chaos
Joonhee Choi, Adam L. Shaw, Ivaylo S. Madjarov, Xin Xie, Ran Finkelstein, Jacob P. Covey, Jordan S. Cotler, Daniel K. Mark, Hsin-Yuan Huang, Anant Kale, Hannes … 展开作者
Joonhee Choi, Adam L. Shaw, Ivaylo S. Madjarov, Xin Xie, Ran Finkelstein, Jacob P. Covey, Jordan S. Cotler, Daniel K. Mark, Hsin-Yuan Huang, Anant Kale, Hannes Pichler, Fernando G. S. L. Brandão, Soonwon Choi, Manuel Endres
Producing quantum states at random has become increasingly important in modern quantum science, with applications both theoretical and practical. In particular, ensembles of such randomly-distributed, but pure, quantum states underly our understanding of complexity in quantum circuits and black holes, and have been used for benchmarking quantum devices in tests of quantum advantage. However, creating random ensembles has necessitated a high degree of spatio-temporal control, placing such studies out of reach for a wide class of quantum systems. Here we solve this problem by predicting and experimentally observing the emergence of random state ensembles naturally under time-independent Hamiltonian dynamics, which we use to implement an efficient, widely applicable benchmarking protocol. The observed random ensembles emerge from projective measurements and are intimately linked to universal correlations built up between subsystems of a larger quantum system, offering new insights into quantum thermalization. Predicated on this discovery, we develop a fidelity estimation scheme, which we demonstrate for a Rydberg quantum simulator with up to 25 atoms using fewer than 10^4 experimental samples. This method has broad applicability, as we show for Hamiltonian parameter estimation, target-state generation benchmarking, and comparison of analog and digital quantum devices. Our work has implications for understanding randomness in quantum dynamics, and enables applications of this concept in a much wider context.
Benchmarking Single-Qubit Gates on a Neutral Atom Quantum Processor
Quantum Technology Centre and Faculty of Physics, M.V. Lomonosov Moscow State University（莫斯科国立大学量子技术中心与物理学院）；Russian Quantum Center（俄罗斯量子中心）；NRC “Kurchatov Institute”（库尔恰托夫国家研究中心）
Asymptotic Metrological Scaling and Concentration in Chaotic Floquet Dynamics
KTH Royal Institute of Technology（皇家理工学院）；Zhejiang University（浙江大学）；Nordita, KTH Royal Institute of Technology and Stockholm University（诺迪塔，皇家理工学院和斯德哥尔摩大学）
Reinforcement Learning for Many-Body Ground-State Preparation Inspired by Counterdiabatic Driving
University of California, Berkeley（加州大学伯克利分校）；Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）；St. Kliment Ohridski University of Sofia（圣基里尔·奥赫里德斯基索菲亚大学）
Cyclotomic Structure and Exact Recurrences in Floquet Many-Body Quantum Dynamics
Institute for Quantum Computing, University of Waterloo（滑铁卢大学量子计算研究所）；Department of Physics and Astronomy, University of Waterloo（滑铁卢大学物理与天文学系）；Department of Physics and Computer Science, Wilfrid Laurier University（威尔弗里德·劳里埃大学物理与计算机科学系）；Perimeter Institute for Theoretical Physics（基础理论物理研究所）
