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arXiv 2309.03301cond-mat.stat-mechmath.PR
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跳跃过程的极值统计

Extreme Value Statistics of Jump Processes

Jérémie Klinger, Raphaël Voituriez, Olivier Bénichou

AI总结:

本文研究一般离散时间连续空间对称跳跃过程的极值统计,通过引入半无穷传播子和带状概率作为核心构件,推导了极值及其达到时间的联合分布,并获得了精确表达式与普适渐近行为。

摘要:

我们研究一般离散时间和连续空间对称跳跃过程的极值统计(EVS)。我们首先证明,对于无界跳跃过程,定义为粒子从0出发,在经过$n$步后位于位置$x$且保持为正的概率的半无穷传播子$G_0(x,n)$,是推导极值及其达到时间的各种联合分布所需的关键要素。除了精确表达式外,我们还提取了这些量的新颖普适渐近行为。对于在首次穿越零点时被杀死的有界、半无穷跳跃过程,我们引入了带状概率$μ_{0,\underline{x}}(n)$,定义为从0出发的粒子保持为正并在其第$n$步恰好达到其最大值$x$的概率。我们证明$μ_{0,\underline{x}}(n)$是解决半无穷跳跃过程EVS的基本构件,并获得了各种联合分布的精确表达式和普适渐近行为。

英文摘要:

We investigate extreme value statistics (EVS) of general discrete time and continuous space symmetric jump processes. We first show that for unbounded jump processes, the semi-infinite propagator $G_0(x,n)$, defined as the probability for a particle issued from $0$ to be at position $x$ after $n$ steps whilst staying positive, is the key ingredient needed to derive a variety of joint distributions of extremes and times at which they are reached. Along with exact expressions, we extract novel universal asymptotic behaviors of such quantities. For bounded, semi-infinite jump processes killed upon first crossing of zero, we introduce the \textit{strip probability} $μ_{0,\underline{x}}(n)$, defined as the probability that a particle issued from 0 remains positive and reaches its maximum $x$ on its $n^{\rm th}$ step exactly. We show that $μ_{0,\underline{x}}(n)$ is the essential building block to address EVS of semi-infinite jump processes, and obtain exact expressions and universal asymptotic behaviors of various joint distributions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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