对于具有重置的扩散搜索过程,步行者的临界数量
Marco Biroli1, Satya N Majumdar1, Grégory Schehr2
1LPTMS, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91405 Orsay, France.
Physical review. E
|July 19, 2023
概括
随机重置可以加快N个布朗运动的搜索过程,但只能达到关键数量的步行者 (N
科学领域:
- 统计物理 统计物理
- 随机过程 随机过程
- 数学生物学 数学生物学
背景情况:
- 布朗运动是扩散的一个基本模型.
- 搜索过程在自然和技术中无处不在.
- 随机重置引入了一个重新启动扩散过程的机制.
研究的目的:
- 为了研究随机重置对N个布朗运动到吸收目标的平均第一通道时间的影响.
- 分析两个不同的重置协议:独立重置和同时重置.
- 确定随机重置增强或阻碍搜索效率的条件.
主要方法:
- 分析表达式的推导为平均首次通道时间.
- 使用Mathematica进行积分的数值评估.
- 通过Langevin模拟验证理论预测.
主要成果:
- 对于N < Nc,存在一个最佳的重置速率 (r*),其中重置是有益的.
- 对于N > Nc,最佳重置率为零,表明重置阻碍了搜索.
- 对于独立和同时重置协议,发现了不同的步行者临界数 (Nc).
结论:
- 随机重置可以优化对有限数量的扩散粒子的搜索过程.
- 重置的有效性取决于粒子数量和重置协议.
- 该研究提供了对优化各种物理和生物系统的搜索策略的见解.
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