The dynamical Ising-Kac model in 3D converges to Φ 3 4.

IF 1.5 1区 数学 Q2 STATISTICS & PROBABILITY
Probability Theory and Related Fields Pub Date : 2025-01-01 Epub Date: 2024-10-15 DOI:10.1007/s00440-024-01316-x
P Grazieschi, K Matetski, H Weber
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引用次数: 0

Abstract

We consider the Glauber dynamics of a ferromagnetic Ising-Kac model on a three-dimensional periodic lattice of size ( 2 N + 1 ) 3 , in which the flipping rate of each spin depends on an average field in a large neighborhood of radius γ - 1 < < N . We study the random fluctuations of a suitably rescaled coarse-grained spin field as N and γ 0 ; we show that near the mean-field value of the critical temperature, the process converges in distribution to the solution of the dynamical Φ 3 4 model on a torus. Our result settles a conjecture from Giacomin et al. (1999). The dynamical Φ 3 4 model is given by a non-linear stochastic partial differential equation (SPDE) which is driven by an additive space-time white noise and which requires renormalisation of the non-linearity. A rigorous notion of solution for this SPDE and its renormalisation is provided by the framework of regularity structures (Hairer in Invent Math 198(2):269-504, 2014. 10.1007/s00222-014-0505-4). As in the two-dimensional case (Mourrat and Weber in Commun Pure Appl Math 70(4):717-812, 2017), the renormalisation corresponds to a small shift of the inverse temperature of the discrete system away from its mean-field value.

三维动态Ising-Kac模型收敛为Φ 34。
我们考虑了尺寸为(2n + 1) 3的三维周期晶格上的铁磁Ising-Kac模型的Glauber动力学,其中每个自旋的翻转速率取决于半径为γ - 1n的大邻域内的平均场。研究了适当重标的粗粒度自旋场在N→∞和γ→0时的随机涨落;在临界温度的平均场值附近,该过程在分布上收敛于环面上的动态Φ 34模型的解。我们的结果证实了Giacomin et al.(1999)的一个猜想。动态Φ 34模型由一个非线性随机偏微分方程(SPDE)给出,该方程由加性时空白噪声驱动,需要对非线性进行重整化。正则结构框架为该SPDE的解及其重整化提供了一个严格的概念(Hairer in Invent Math 198(2):269- 504,2014)。10.1007 / s00222 - 014 - 0505 - 4)。在二维情况下(Mourrat和Weber在common Pure Appl Math 70(4):717- 812,2017),重整化对应于离散系统的逆温度从其平均场值的小位移。
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来源期刊
Probability Theory and Related Fields
Probability Theory and Related Fields 数学-统计学与概率论
CiteScore
3.70
自引率
5.00%
发文量
71
审稿时长
6-12 weeks
期刊介绍: Probability Theory and Related Fields publishes research papers in modern probability theory and its various fields of application. Thus, subjects of interest include: mathematical statistical physics, mathematical statistics, mathematical biology, theoretical computer science, and applications of probability theory to other areas of mathematics such as combinatorics, analysis, ergodic theory and geometry. Survey papers on emerging areas of importance may be considered for publication. The main languages of publication are English, French and German.
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