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arXiv 1706.01675cond-mat.stat-mechmath-phmath.MP
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分数阶布朗运动的广义反正弦律

Generalized arcsine laws for fractional Brownian motion

Tridib Sadhu, Mathieu Delorme, Kay Jörg Wiese

摘要:

布朗运动的三个反正弦定律是极值统计学的基石。对于从原点开始并在时间$T$期间演化的布朗$B_t$,考虑以下三个可观测量:(i)过程为正的持续时间$t_+$,(ii)过程最后访问原点的时间$t_{\rm last}$,以及(iii)当它达到其最大值(或最小值)时的时间$t_{\rm max}$。所有三个观测值都有相同的累积概率分布,表示为反正弦函数,因此称为反正弦定律。我们展示了这些法律如何改变分数布朗运动$X_t$,一个非马尔可夫高斯过程的赫斯特指数$H$。它推广了标准布朗运动(即$H=\tfrac{1}{2}$)。我们得到的三个概率使用微扰展开在$ε= H-\tfrac{1}{2}$。虽然所有三个概率都不同,但这种区别只能在$ε$中的二阶进行。通过大量的数值模拟,我们的结果被证实具有很高的精度。

英文摘要:

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 $t_{\rm last}$ the process last visits the origin, and (iii) the time $t_{\rm max}$ when it achieves its maximum (or minimum). All three observables have the same cumulative probability distribution expressed as an arcsine function, thus the name of 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. $H=\tfrac{1}{2}$). We obtain the three probabilities using a perturbative expansion in $ε= H-\tfrac{1}{2}$. 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.

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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