Tata Institute of Fundamental Research, Mumbai 400005, India.
CNRS-Laboratoire de Physique Théorique de l'Ecole Normale Supérieure, PSL Research University, Sorbonne Universités, UPMC, 24 rue Lhomond, 75005 Paris, France.
Phys Rev Lett. 2018 Jan 26;120(4):040603. doi: 10.1103/PhysRevLett.120.040603.
The three arcsine laws for Brownian motion are a cornerstone of extreme-value statistics. For a Brownian B_{t} starting from the origin, and evolving during time T, one considers the following three observables: (i) the duration t_{+} the process is positive, (ii) the time t_{last} the process last visits the origin, and (iii) the time t_{max} when it achieves its maximum (or minimum). All three observables have the same cumulative probability distribution expressed as an arcsine function, thus the name arcsine laws. We show how these laws change for fractional Brownian motion X_{t}, a non-Markovian Gaussian process indexed by the Hurst exponent H. It generalizes standard Brownian motion (i.e., H=1/2). We obtain the three probabilities using a perturbative expansion in ϵ=H-1/2. While all three probabilities are different, this distinction can only be made at second order in ϵ. Our results are confirmed to high precision by extensive numerical simulations.
布朗运动的三个反正弦定律是极值统计的基石。对于一个从原点开始并在时间 T 内演化的布朗运动 B_{t},我们考虑以下三个可观测量:(i)过程为正的持续时间 t_{+},(ii)过程最后一次访问原点的时间 t_{last},以及(iii)过程达到最大值(或最小值)的时间 t_{max}。这三个可观测量具有相同的累积概率分布,表现为反正弦函数,因此得名反正弦定律。我们展示了这些定律如何针对分数布朗运动 X_{t}发生变化,分数布朗运动是一个由赫斯特指数 H 索引的非马尔可夫高斯过程。它推广了标准布朗运动(即 H=1/2)。我们使用 ϵ=H-1/2 的微扰展开式来获得这三个概率。尽管所有三个概率都不同,但这种区别只能在 ϵ 的二阶中观察到。我们的结果通过广泛的数值模拟得到了高精度的验证。