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Expediting Feller process with stochastic resetting
Physical Review E ( IF 2.2 ) Pub Date : 2022-09-26 , DOI: 10.1103/physreve.106.034133
Somrita Ray 1
Affiliation  

We explore the effect of stochastic resetting on the first-passage properties of the Feller process. The Feller process can be envisioned as space-dependent diffusion, with diffusion coefficient D(x)=x, in a potential U(x)=x(x2θ) that owns a minimum at θ. This restricts the process to the positive side of the origin and therefore, Feller diffusion can successfully model a vast array of phenomena in biological and social sciences, where realization of negative values is forbidden. In our analytically tractable model system, a particle that undergoes Feller diffusion is subject to Poissonian resetting, i.e., taken back to its initial position at a constant rate r, after random time epochs. We addressed the two distinct cases that arise when the relative position of the absorbing boundary (xa) with respect to the initial position of the particle (x0) differ, i.e., for (a) x0<xa and (b) xa<x0. Utilizing the Fokker-Planck description of the system, we obtained closed-form expressions for the Laplace transform of the survival probability and hence derived the exact expressions of the mean first-passage time Tr. Performing a comprehensive analysis on the optimal resetting rate (r) that minimize Tr and the maximal speedup that r renders, we identify the phase space where Poissonian resetting facilitates first-passage for Feller diffusion. We observe that for x0<xa, resetting accelerates first-passage when θ<θc, where θc is a critical value of θ that decreases when xa is moved away from the origin. In stark contrast, for xa<x0, resetting accelerates first-passage when θ>θc, where θc is a critical value of θ that increases when x0 is moved away from the origin. Our study opens up the possibility of a series of subsequent works with more case-specific models of Feller diffusion with resetting.

中文翻译:

通过随机重置加速 Feller 过程

我们探讨了随机重置对 Feller 过程第一通道特性的影响。Feller 过程可以设想为空间相关扩散,具有扩散系数D(X)=X, 在一个潜在的ü(X)=X(X2-θ)拥有最低θ. 这将过程限制在原点的积极方面,因此,费勒扩散可以成功地模拟生物和社会科学中的大量现象,其中禁止实现负值。在我们的分析易处理模型系统中,经历费勒扩散的粒子会受到泊松重置,即以恒定速率回到其初始位置r,在随机时间之后。我们解决了当吸收边界的相对位置(X一个) 相对于粒子的初始位置 (X0) 不同,即对于 (a)X0<X一个(b)X一个<X0. 利用系统的福克-普朗克描述,我们得到了生存概率的拉普拉斯变换的闭式表达式,从而推导出了平均首过时间的精确表达式r. 对最优复位率进行综合分析(r) 最小化r和最大加速r渲染,我们确定了泊松重置促进费勒扩散的第一通道的相空间。我们观察到对于X0<X一个, 重置会加速第一次通过时θ<θC, 在哪里θC是一个临界值θX一个被移离原点。形成鲜明对比的是,对于X一个<X0, 重置会加速第一次通过时θ>θC, 在哪里θC是一个临界值θX0被移离原点。我们的研究开辟了一系列后续工作的可能性,这些工作具有更多特定案例的 Feller 扩散和重置模型。
更新日期:2022-09-26
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