Zipping many-body quantum states: a scalable approach to diagonal entropy

Fuente: arXiv
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Main Authors: Chen, Yu-Hsueh, Grover, Tarun
Format: Preprint
Published: 2025
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author Chen, Yu-Hsueh
Grover, Tarun
author_facet Chen, Yu-Hsueh
Grover, Tarun
contents The outcomes of projective measurements on a quantum many-body system in a chosen basis are inherently probabilistic. The Shannon entropy of this probability distribution (the "diagonal entropy") often reveals universal features, such as the existence of a quantum phase transition. A brute-force tomographic approach to estimating this entropy scales exponentially with the system size. Here, we explore using the Lempel-Ziv lossless image compression algorithm as an efficient, scalable alternative, readily implementable in a quantum gas microscope or programmable quantum devices. We test this approach on several examples: one-dimensional quantum Ising model, and two-dimensional states that display conventional symmetry breaking due to quantum fluctuations, or strong-to-weak symmetry-breaking due to local decoherence. We also employ the diagonal mixed state to put constraints on the phase boundaries of our models. In all examples, the compression method accurately recovers the entropy density while requiring at most polynomially many images. We also analyze the singular part of the diagonal entropy density using renormalization group on a replicated action. In the 1+1-D quantum Ising model, we find that it scales as $|t| \log|t|$, where $t$ is the deviation from the critical point, while in a 2+1-D state with amplitudes proportional to the Boltzmann weight of the 2D Ising model, it follows a $t^2 \log|t|$ scaling.
format Preprint
id arxiv_https___arxiv_org_abs_2502_18898
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Zipping many-body quantum states: a scalable approach to diagonal entropy
Chen, Yu-Hsueh
Grover, Tarun
Quantum Physics
Disordered Systems and Neural Networks
Quantum Gases
Statistical Mechanics
Strongly Correlated Electrons
The outcomes of projective measurements on a quantum many-body system in a chosen basis are inherently probabilistic. The Shannon entropy of this probability distribution (the "diagonal entropy") often reveals universal features, such as the existence of a quantum phase transition. A brute-force tomographic approach to estimating this entropy scales exponentially with the system size. Here, we explore using the Lempel-Ziv lossless image compression algorithm as an efficient, scalable alternative, readily implementable in a quantum gas microscope or programmable quantum devices. We test this approach on several examples: one-dimensional quantum Ising model, and two-dimensional states that display conventional symmetry breaking due to quantum fluctuations, or strong-to-weak symmetry-breaking due to local decoherence. We also employ the diagonal mixed state to put constraints on the phase boundaries of our models. In all examples, the compression method accurately recovers the entropy density while requiring at most polynomially many images. We also analyze the singular part of the diagonal entropy density using renormalization group on a replicated action. In the 1+1-D quantum Ising model, we find that it scales as $|t| \log|t|$, where $t$ is the deviation from the critical point, while in a 2+1-D state with amplitudes proportional to the Boltzmann weight of the 2D Ising model, it follows a $t^2 \log|t|$ scaling.
title Zipping many-body quantum states: a scalable approach to diagonal entropy
topic Quantum Physics
Disordered Systems and Neural Networks
Quantum Gases
Statistical Mechanics
Strongly Correlated Electrons
url https://arxiv.org/abs/2502.18898