Searcharxiv⌕ Search

arXiv · 2610.10467

Effective-Geometry Rescaling and Universal Critical Behavior in the Anisotropic Three-State Potts Model on the Square Lattice

Abstract

We study the two-dimensional anisotropic three-state Potts ferromagnet on the square lattice using Wolff single-cluster Monte Carlo simulations and finite-size scaling. For coupling ratios $λ=J_y/J_x=0.5$, $0.75$, and $1$, finite-size scaling of the correlation ratio yields critical behavior consistent with the two-dimensional three-state Potts universality class. The scaling of the leading Fisher zeros gives a correlation-length exponent consistent with $ν=5/6$, while their cumulative density is consistent with the expected specific-heat exponent $α=1/3$. We further characterize the anisotropy at criticality using directional correlation ratios $R_x$ and $R_y$ together with directional FK wrapping probabilities. For $λ=0.5$ on a physically square lattice, $R_x$ and $R_y$ approach distinct critical values while yielding a common correlation-length exponent. From the wrapping probabilities, we independently determine an effective aspect ratio $ρ_e^\square=0.6413(5)$, in close agreement with the theoretical value $ρ_e^{\square,\mathrm{th}}\simeq0.64150030$ obtained from the isoradial representation. Using the theoretical value to set the physical aspect ratio restores directional equivalence, $R_x\simeq R_y$, and brings the overall correlation ratio toward the isotropic-square reference. The results show that spatial anisotropy changes the effective critical geometry without altering the bulk three-state Potts universality class.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Fan Yang, Jian Gao, Lu Liu, Yuhai Liu. 2026-10-07. Effective-Geometry Rescaling and Universal Critical Behavior in the Anisotropic Three-State Potts Model on the Square Lattice. https://arxiv.org/abs/2610.10467

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Optimizing optimal transport: Role of final distributions in finite-time thermodynamics

Performing thermodynamic tasks within finite time while minimizing thermodynamic costs is a central challenge in stochastic thermodynamics. Here, we develop a unified framework for optimizing the thermodynamic cost of performing various tasks in finite time for overdamped Langevin systems. Conventional optimization of thermodynamic cost based on optimal transport theory leaves room for varying the final distributions according to the intended task, enabling further optimization. Taking advantage of this freedom, we use Lagrange multipliers to derive the optimal final distribution that minimizes the thermodynamic cost. Our framework applies to a wide range of thermodynamic tasks, including particle transport, thermal squeezing, and information processing such as information erasure, measurement, and feedback. Our results are expected to provide design principles for information-processing devices and thermodynamic machines that operate at high speed with low energetic costs.

cond-mat.stat-mech↗

Non-Markovian escape under stochastic resetting

Stochastic resetting is a powerful strategy known to optimize target-search processes at microscopic scales. While its effects on Markovian systems are well understood, its influence on memory-driven systems, such as in viscoelastic baths, has not been adequately investigated. In this work, we study the first-passage properties of escape for a harmonically trapped particle in a non-Markovian environment under stochastic resetting. We employ a complete renewal approach and find that the characteristic non-exponential heavy tail of the first passage time (FPT) distribution becomes exponential when resetting is introduced. We further find that optimal resetting is achievable at a lower reset rate when the dynamics are weakly correlated; however, for stronger correlations, the process needs to be reset more frequently. Therefore, resetting in memory-driven dynamics can be used as an effective control strategy to initiate faster escape, thereby regulating efficient transport mechanisms in complex chemical and biomolecular environments that follow non-Markovian dynamics.

cond-mat.stat-mech↗

Violation of the method of images in non-Markovian processes and its connection to stochastic heat

This article discusses a failure of the widely used method of images to describe the time evolution of probability distributions in diffusive processes with memory. A walker in one-dimensional space draws a dead or a surviving path depending on whether it has touched a target during stochastic evolution. For the dead walker, we define its conjugate twin paired by paths spatially reflected at the first passage time. The probability distribution of the reflected dead path coincides with that of the free image walker in a physical domain, but not generally with that of the original dead walker for non-Markovian processes, which violates the method of images. For systems reducible to the generalized Langevin equation with the fluctuation-dissipation relation, we propose an energetic interpretation in terms of a path-memory force, where the path-probability ratio of the dead to the reflected path obeys an analogous relation to the fluctuation theorem associated with heat from the reflected to the original dead walker. This framework provides a quantitative basis as well as an intuitive picture of how and why the method of images breaks down for non-Markovian processes.

cond-mat.stat-mech↗