具有非梯度漂移力和各向异性势的非线性Fokker-Planck方程。

IF 3.2 2区 数学 Q1 MATHEMATICS, APPLIED
Chaos Pub Date : 2025-09-01 DOI:10.1063/5.0280921
V T F de Luca, R S Wedemann, A R Plastino
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引用次数: 0

摘要

关于非线性福克-普朗克方程描述的物理现象的研究通常考虑作用于所研究的物理系统的漂移力由势函数的梯度导出的情况。在本文中,我们研究了非线性Fokker-Planck方程,其中漂移场有一个分量来自不对称势的梯度,另一个分量对应于非梯度力项。我们考虑二维非线性Fokker-Planck方程的特殊情况,其中漂移场是由各向异性谐波势获得的,除了非梯度项。我们分析了该演化方程允许q指数平稳解的条件。我们证明了该方程允许q-高斯,时间相关的解演化为平稳形式,并讨论了它们的一些重要性质。将演化的概率密度解释为描述粒子系综,我们推导并数值研究了伴随轨迹。本文讨论的理论框架极大地扩大了基于sq的非线性Fokker-Planck形式主义在物理学、生物学、经济学、人工神经网络和其他领域的各种复杂系统问题研究中的可能应用范围。重要的是,它使我们能够解决元素之间的相互作用不对称的系统建模问题,例如,在大脑的神经网络中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The nonlinear Fokker-Planck equation with nongradient drift forces and an anisotropic potential.

Studies regarding physical phenomena described by nonlinear Fokker-Planck equations usually consider the case where the drift forces acting on the physical system under investigation are derived from the gradient of a potential function. In the present manuscript, we investigate nonlinear Fokker-Planck equations, where the drift field has a component that is derived from the gradient of an asymmetric potential and another that corresponds to a nongradient force term. We consider the specific case of a two-dimensional, nonlinear Fokker-Planck equation where the drift field is obtained from an anisotropic, harmonic potential, besides the nongradient term. We analyze the conditions under which this evolution equation admits stationary solutions that are q-exponentials. We prove that this equation admits q-Gaussian, time-dependent solutions that evolve to stationary forms and discuss some of their important properties. Interpreting the evolving probability densities as describing an ensemble of particles, we derived and numerically studied the concomitant trajectories. The theoretical framework discussed in the present contribution enlarges substantially the range of possible applications of the Sq-based, nonlinear Fokker-Planck formalism to the study of problems in diverse types of complex systems in physics, biology, economics, artificial neural networks, and other areas. Importantly, it allows us to approach the problem of modeling systems where the interaction among elements are not symmetrical, as is the case, for example, in neural networks of the brain.

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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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