随机性
统计物理学
扩散
蒙特卡罗方法
扩散过程
分布(数学)
随机过程
数学
对象(语法)
反常扩散
点(几何)
时空
比例(比率)
粒子(生态学)
功能(生物学)
物理
分布函数
粒子数
差异(会计)
点过程
相关函数(量子场论)
碎片(计算)
空格(标点符号)
首次命中时间模型
粒子系统
国家(计算机科学)
理论(学习稳定性)
布朗运动
班级(哲学)
过程(计算)
概率密度函数
泊松点过程
概率分布
时空
作者
H.Y. Wang,G. W. Slater
标识
DOI:10.1016/j.physa.2026.131643
摘要
We explore the time required for a densely packed, single-file diffusion system, originating from the fragmentation of an object, to expand to a point where each particle can be distinctly identified. We use Monte Carlo methods to investigate this class of problems and define the time taken to reach the required final state as a relative first-passage spreading time . Our results show that the stochastic nature of the diffusion process is as important as the details of the particle size distribution when it comes to determining the spreading time. Nevertheless, we introduce a distribution randomness parameter, Z , which is linearly correlated with the final spreading time. By studying the correlation between the time required for particles to disperse and the final space they cover, we identify the fundamental length scale that governs this phenomenon. Finally, we show that the distribution function of spreading times follows a well-known form for first-passage time problems, and that its variance decreases linearly with the number of particles.
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