带漂移的次分式布朗运动中的反常扩散、非高斯性和非遍历性
Anomalous diffusion, non-Gaussianity, and nonergodicity for subordinated fractional Brownian motion with a drift
AI总结：
研究带漂移的次分式布朗运动，通过次ordination引入捕获，分析其非高斯性与非遍历性，并与模拟验证，比较有无漂移的差异。
摘要：
考虑在无序介质中，具有长程相关增量（运动阶段）的粒子随机运动，该运动被间歇性的固定（捕获阶段）所中断，并存在外部漂移。特别地，我们考虑捕获事件的时间服从具有发散平均捕获时间的无标度分布。我们通过分数布朗运动（FBM）在恒定强迫下构建此过程，其中捕获效应通过次ordination技术引入，将“操作时间”与可观测的“真实时间”联系起来。我们推导了该过程的统计性质，如非高斯性和非遍历性，针对系综平均和单轨迹（时间）平均。我们展示了与大量模拟在概率密度函数、偏度、峰度以及系综和时间平均均方位移上的良好一致性。我们特别强调了有漂移和无漂移情况之间的比较。
英文摘要：
The stochastic motion of a particle with long-range correlated increments (the moving phase) which is intermittently interrupted by immobilizations (the traping phase) in a disordered medium is considered in the presence of an external drift. In particular, we consider trapping events whose times follow a scale-free distribution with diverging mean trapping time. We construct this process in terms of fractional Brownian motion (FBM) with constant forcing in which the trapping effect is introduced by the subordination technique, connecting "operational time" with observable "real time". We derive the statistical properties of this process such as non-Gaussianity and non-ergodicity, for both ensemble and single-trajectory (time) averages. We demonstrate nice agreement with extensive simulations for the probability density function, skewness, kurtosis, as well as ensemble and time-averaged mean squared displacements. We pay specific emphasis on the comparisons between the cases with and without drift.
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。
