Efficient Classical Shadow Tomography through Many-body Localization Dynamics

Fuente: arXiv
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Autori principali: Zhou, Tian-Gang, Zhang, Pengfei
Natura: Preprint
Pubblicazione: 2023
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author Zhou, Tian-Gang
Zhang, Pengfei
author_facet Zhou, Tian-Gang
Zhang, Pengfei
contents Classical shadow tomography serves as a potent tool for extracting numerous properties from quantum many-body systems with minimal measurements. Nevertheless, prevailing methods yielding optimal performance for few-body operators necessitate the application of random two-qubit gates, a task that can prove challenging on specific quantum simulators such as ultracold atomic gases. In this work, we introduce an alternative approach founded on the dynamics of many-body localization, a phenomenon extensively demonstrated in optical lattices. Through an exploration of the shadow norm -- both analytically, employing a phenomenological model, and numerically, utilizing the TEBD algorithm -- we demonstrate that our scheme achieves remarkable efficiency comparable to shallow circuits or measurement-induced criticality, resulting in a significant improvement in the exponential exponent compared to the previous classical shadow protocol. Our findings are corroborated through direct numerical simulations encompassing the entire sampling and reconstruction processes. Consequently, our results present a compelling methodology for analyzing the output states of quantum simulators.
format Preprint
id arxiv_https___arxiv_org_abs_2309_01258
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Efficient Classical Shadow Tomography through Many-body Localization Dynamics
Zhou, Tian-Gang
Zhang, Pengfei
Quantum Physics
Disordered Systems and Neural Networks
Quantum Gases
Statistical Mechanics
Classical shadow tomography serves as a potent tool for extracting numerous properties from quantum many-body systems with minimal measurements. Nevertheless, prevailing methods yielding optimal performance for few-body operators necessitate the application of random two-qubit gates, a task that can prove challenging on specific quantum simulators such as ultracold atomic gases. In this work, we introduce an alternative approach founded on the dynamics of many-body localization, a phenomenon extensively demonstrated in optical lattices. Through an exploration of the shadow norm -- both analytically, employing a phenomenological model, and numerically, utilizing the TEBD algorithm -- we demonstrate that our scheme achieves remarkable efficiency comparable to shallow circuits or measurement-induced criticality, resulting in a significant improvement in the exponential exponent compared to the previous classical shadow protocol. Our findings are corroborated through direct numerical simulations encompassing the entire sampling and reconstruction processes. Consequently, our results present a compelling methodology for analyzing the output states of quantum simulators.
title Efficient Classical Shadow Tomography through Many-body Localization Dynamics
topic Quantum Physics
Disordered Systems and Neural Networks
Quantum Gases
Statistical Mechanics
url https://arxiv.org/abs/2309.01258