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Related papers: The Airy$_2$ process and the 3D Ising model

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We study the dynamics of a class of two dimensional stochastic processes, depending on two parameters, which may be interpreted as two different temperatures, respectively associated to interfacial and to bulk noise. Special lines in the…

Statistical Mechanics · Physics 2009-10-31 J-M Drouffe , C Godreche

This paper presents an {\it ab initio} derivation of the expression given by irreversible thermodynamics for the rate of entropy production for different classes of diffusive processes. The first class are Lorentz gases, where…

Chaotic Dynamics · Physics 2009-11-07 J. R. Dorfman , P. Gaspard , T. Gilbert

We consider the limiting behavior of fluctuations of small noise diffusions with multiple scales around their homogenized deterministic limit. We allow full dependence of the coefficients on the slow and fast motion. These processes arise…

Probability · Mathematics 2015-02-20 Konstantinos Spiliopoulos

We apply extensive Monte Carlo simulations to study the probability distribution $P(m)$ of the order parameter $m$ for the simple cubic Ising model with periodic boundary condition at the transition point. Sampling is performed with the…

Computational Physics · Physics 2020-03-18 Jiahao Xu , Alan M. Ferrenberg , David P. Landau

The use of a transfer matrix method to solve the 3D Ising model is straightforwardly generalized from the 2D case. We follow B.Kaufman's approach. No approximation is made, however the largest eigenvalue cannot be identified. This problem…

Statistical Mechanics · Physics 2007-05-23 S. L. Lou , S. H. Wu

A noncolliding diffusion process is a conditional process of $N$ independent one-dimensional diffusion processes such that the particles never collide with each other. This process realizes an interacting particle system with long-ranged…

Probability · Mathematics 2011-10-21 Makoto Katori , Hideki Tanemura

Diffusion-based generative models (DBGMs) perturb data to a target noise distribution and reverse this process to generate samples. The choice of noising process, or inference diffusion process, affects both likelihoods and sample quality.…

Machine Learning · Computer Science 2023-03-06 Raghav Singhal , Mark Goldstein , Rajesh Ranganath

We discuss several examples of point processes (all taken from Hough, Krishnapur, Peres, Vir\'ag (2009)) for which the autocorrelation and diffraction measures can be calculated explicitly. These include certain classes of determinantal and…

Mathematical Physics · Physics 2015-07-22 Michael Baake , Holger Kösters , Robert V. Moody

The Airy$_{\beta }$ random point fields ($ \beta = 1,2,4$) are random point fields emerging as the soft-edge scaling limits of eigenvalues of Gaussian random matrices. We construct the unlabeled diffusion reversible with respect to the…

Probability · Mathematics 2024-07-30 Hirofumi Osada , Hideki Tanemura

In this paper, we are interested in a general equation that has finite speed of propagation compatible with Einstein's theory of special relativity. This equation without external force fields has been derived recently by means of optimal…

Analysis of PDEs · Mathematics 2015-08-18 Manh Hong Duong

A variety of researchers have successfully obtained the parameters of low dimensional diffusion models using the data that comes out of atomistic simulations. This naturally raises a variety of questions about efficient estimation,…

Statistical Mechanics · Physics 2015-11-06 Christopher P. Calderon

We study in detail the active Ising model, a stochastic lattice gas where collective motion emerges from the spontaneous breaking of a discrete symmetry. On a 2d lattice, active particles undergo a diffusion biased in one of two possible…

Statistical Mechanics · Physics 2015-10-12 A. P. Solon , J. Tailleur

Diffusion probabilistic models excel at sampling new images from learned distributions. Originally motivated by drift-diffusion concepts from physics, they apply image perturbations such as noise and blur in a forward process that results…

Image and Video Processing · Electrical Eng. & Systems 2024-06-07 Pascal Peter

In the series of models with interacting particles in stochastic geometry, a new contribution presents the facet process which is defined in arbitrary Euclidean dimension. In 2D, 3D specially it is a process of interacting segments, flat…

Probability · Mathematics 2015-04-02 Jakub Vecera , Viktor Benes

We prove a Large Deviations Principle (LDP) for systems of diffusions (particles) interacting through their ranks, when the number of particles tends to infinity. We show that the limiting particle density is given by the unique solution of…

Probability · Mathematics 2017-04-05 Amir Dembo , Mykhaylo Shkolnikov , S. R. Srinivasa Varadhan , Ofer Zeitouni

We study the inductive biases of diffusion models with a conditioning-variable, which have seen widespread application as both text-conditioned generative image models and observation-conditioned continuous control policies. We observe that…

Machine Learning · Computer Science 2025-12-23 Daniel Pfrommer , Zehao Dou , Christopher Scarvelis , Max Simchowitz , Ali Jadbabaie

In this article we make first steps in coupling matter to causal set theory in the path integral. We explore the case of the Ising model coupled to the 2d discrete Einstein Hilbert action, restricted to the 2d orders. We probe the phase…

General Relativity and Quantum Cosmology · Physics 2018-03-28 Lisa Glaser

This paper investigates pattern formation in reaction--diffusion systems with both diffusive and nondiffusive components, providing necessary and sufficient conditions for diffusion-driven instability (DDI) and establishing the existence of…

Analysis of PDEs · Mathematics 2026-05-07 Théo André , Szymon Cygan , Anna Marciniak-Czochra , Finn Münnich

This note proves an upper bound for the fluctuations of a second-class particle in the totally asymmetric simple exclusion process. The proof needs a lower tail estimate for the last-passage growth model associated with the exclusion…

Probability · Mathematics 2007-05-23 Timo Seppalainen

This paper introduces a framework for simulating finite dimensional representations of (jump) diffusion sample paths over finite intervals, without discretisation error (exactly), in such a way that the sample path can be restored at any…

Methodology · Statistics 2016-02-10 Murray Pollock , Adam M. Johansen , Gareth O. Roberts
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