Non-Gaussian behavior in fractional Laplace motion with drift

被引:0
|
作者
Wang, Wei [1 ]
Liang, Yingjie [1 ,2 ]
Chechkin, Aleksei V. [1 ,3 ,4 ,5 ]
Metzler, Ralf [1 ,5 ]
机构
[1] Univ Potsdam, Inst Phys & Astron, D-14476 Potsdam, Germany
[2] Hohai Univ, Coll Mech & Engn Sci, Nanjing 211100, Peoples R China
[3] Wroclaw Univ Sci & Technol, Fac Pure & Appl Math, Hugo Steinhaus Ctr, PL-50370 Wroclaw, Poland
[4] Max Planck Inst Microstruct Phys, German Ukrainian Core Excellence, Weinberg 2, D-06120 Halle, Germany
[5] Asia Pacific Ctr Theoret Phys, Pohang 37673, South Korea
基金
中国国家自然科学基金;
关键词
SINGLE-PARTICLE TRACKING; TIME RANDOM-WALKS; ANOMALOUS DIFFUSION; LEVY; DISPERSION; EQUATIONS; MODEL;
D O I
10.1103/PhysRevE.111.034121
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
We study fractional Laplace motion (FLM) obtained from subordination of fractional Brownian motion (FBM) to a gamma process in the presence of an external drift that acts on the composite process or of an internal drift acting solely on the parental process. We derive the statistical properties of this FLM process and find that the external drift does not influence the mean-squared displacement, whereas the internal drift leads to normal diffusion, dominating at long times in the subdiffusive Hurst exponent regime. We also investigate the intricate properties of the probability density function (PDF), demonstrating that it possesses a central Gaussian region whose expansion in time is influenced by FBM's Hurst exponent. Outside of this region, the PDF follows a non-Gaussian pattern. The kurtosis of this FLM process converges toward the Gaussian limit at long times insensitive to the extreme non-Gaussian tails. Additionally, in the presence of the external drift, the PDF remains symmetric and centered at x = vt. In contrast, for the internal drift this symmetry is broken. The results of our computer simulations are fully consistent with the theoretical predictions. The FLM model is suitable for describing stochastic processes with a non-Gaussian PDF and long-ranged correlations of the motion.
引用
收藏
页数:15
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