About the Optimal FPE for Non-linear 1d-SDE with Gaussian Noise: The Pitfall of the Perturbative Approach

IF 1.3 3区 物理与天体物理 Q3 PHYSICS, MATHEMATICAL Journal of Statistical Physics Pub Date : 2024-02-15 DOI:10.1007/s10955-023-03228-x
Marco Bianucci, Mauro Bologna, Riccardo Mannella
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Abstract

This paper deals with the problem of finding the Fokker Planck Equation (FPE) for the single-time probability density function (PDF) that optimally approximates the single-time PDF of a 1-D Stochastic Differential Equation (SDE) with Gaussian correlated noise. In this context, we tackle two main tasks. First, we consider the case of weak noise and in this framework we give a formal ground to the effective correction, introduced elsewhere (Bianucci and Mannella in J Phys Commun 4(10):105019, 2020, https://doi.org/10.1088/2399-6528/abc54e), to the Best Fokker Planck Equation (a standard “Born-Oppenheimer” result), also covering the more general cases of multiplicative SDE. Second, we consider the FPE obtained by using the Local Linearization Approach (LLA), and we show that a generalized cumulant approach allows an understanding of why the LLA FPE performs so well, even for noises with long (but finite) time scales and large intensities.

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关于具有高斯噪声的非线性 1d-SDE 的最佳 FPE:惯性方法的陷阱
本文讨论的问题是为单次概率密度函数(PDF)寻找福克-普朗克方程(FPE),以最佳方式逼近具有高斯相关噪声的一维随机微分方程(SDE)的单次 PDF。在这种情况下,我们主要解决两个问题。首先,我们考虑了弱噪声的情况,并在此框架内给出了有效校正的形式基础(Bianucci 和 Mannella 在 J Phys Commun 4(10):105019, 2020, https://doi.org/10.1088/2399-6528/abc54e),该校正在其他地方引入了最佳福克-普朗克方程(一个标准的 "Born-Oppenheimer "结果),也涵盖了乘法 SDE 的更一般情况。其次,我们考虑了使用局部线性化方法(LLA)得到的 FPE,并表明广义累积法可以理解为什么 LLA FPE 即使在时间尺度较长(但有限)和强度较大的噪声中也表现如此出色。
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来源期刊
Journal of Statistical Physics
Journal of Statistical Physics 物理-物理:数学物理
CiteScore
3.10
自引率
12.50%
发文量
152
审稿时长
3-6 weeks
期刊介绍: The Journal of Statistical Physics publishes original and invited review papers in all areas of statistical physics as well as in related fields concerned with collective phenomena in physical systems.
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