Bressloff Paul C
Department of Mathematics, University of Utah, Salt Lake City, Utah 84112, USA.
Phys Rev E. 2016 Oct;94(4-1):042129. doi: 10.1103/PhysRevE.94.042129. Epub 2016 Oct 21.
We analyze the stochastic dynamics of a large population of noninteracting particles driven by a common environmental input in the form of an Ornstein-Uhlenbeck (OU) process. The density of particles evolves according to a stochastic Fokker-Planck (FP) equation with respect to different realizations of the OU process. We then exploit the connection with previous work on diffusion in randomly switching environments in order to derive moment equations for the distribution of solutions to the stochastic FP equation. We use perturbation theory and Green's functions to calculate the mean and variance of the distribution when the relaxation rate of the OU process is fast (close to the white-noise limit). Finally, we show how the theory of noise-induced synchronization can be recast into the framework of a stochastic FP equation.
我们分析了由奥恩斯坦 - 乌伦贝克(OU)过程形式的共同环境输入驱动的大量非相互作用粒子的随机动力学。粒子密度根据关于OU过程不同实现的随机福克 - 普朗克(FP)方程演化。然后,我们利用与先前关于随机切换环境中扩散的工作的联系,以推导随机FP方程解的分布的矩方程。当OU过程的弛豫率很快(接近白噪声极限)时,我们使用微扰理论和格林函数来计算分布的均值和方差。最后,我们展示了噪声诱导同步理论如何能够被重铸到随机FP方程的框架中。