Probing phase transitions with correlations in configuration space

Fuente: arXiv
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Auteurs principaux: Su, Wen-Yu, Liu, Yu-Jing, Ma, Nvsen, Cheng, Chen
Format: Preprint
Publié: 2024
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author Su, Wen-Yu
Liu, Yu-Jing
Ma, Nvsen
Cheng, Chen
author_facet Su, Wen-Yu
Liu, Yu-Jing
Ma, Nvsen
Cheng, Chen
contents In principle, the probability of configurations, determined by the system's partition function or wave function, encapsulates essential information about phases and phase transitions. Despite the exponentially large configuration space, we show that the generic correlation of distances between configurations, with a degree of freedom proportional to the lattice size, can probe phase transitions using importance sampling procedures like Monte Carlo simulations. The distribution of sampled distances varies significantly across different phases, suggesting universal critical behavior for uncertainty and participation entropy. For various classical spin models with different phases and transitions, finite-size analysis based on these quantities accurately identifies phase transitions and critical points. Notably, in all cases, the critical exponent derived from the uncertainty of distances equals the anomalous dimension governing real-space correlation decay. Thus, configuration space correlations, defined by distance uncertainties, share the same decay ratio as real-space correlations, determining the universality class of phase transitions. This work applies to diverse lattice models with different local degrees of freedom, e.g., two levels for Ising-like models, discrete multi-levels for q-state clock models, and continuous local levels for the XY model, offering a robust, alternative method for understanding complex phases and transitions.
format Preprint
id arxiv_https___arxiv_org_abs_2404_07087
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Probing phase transitions with correlations in configuration space
Su, Wen-Yu
Liu, Yu-Jing
Ma, Nvsen
Cheng, Chen
Statistical Mechanics
In principle, the probability of configurations, determined by the system's partition function or wave function, encapsulates essential information about phases and phase transitions. Despite the exponentially large configuration space, we show that the generic correlation of distances between configurations, with a degree of freedom proportional to the lattice size, can probe phase transitions using importance sampling procedures like Monte Carlo simulations. The distribution of sampled distances varies significantly across different phases, suggesting universal critical behavior for uncertainty and participation entropy. For various classical spin models with different phases and transitions, finite-size analysis based on these quantities accurately identifies phase transitions and critical points. Notably, in all cases, the critical exponent derived from the uncertainty of distances equals the anomalous dimension governing real-space correlation decay. Thus, configuration space correlations, defined by distance uncertainties, share the same decay ratio as real-space correlations, determining the universality class of phase transitions. This work applies to diverse lattice models with different local degrees of freedom, e.g., two levels for Ising-like models, discrete multi-levels for q-state clock models, and continuous local levels for the XY model, offering a robust, alternative method for understanding complex phases and transitions.
title Probing phase transitions with correlations in configuration space
topic Statistical Mechanics
url https://arxiv.org/abs/2404.07087