Kuśmierz Łukasz, Dybiec Bartłomiej, Gudowska-Nowak Ewa
Laboratory for Neural Computation and Adaptation, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.
Marian Smoluchowski Institute of Physics and Mark Kac Complex Systems Research Center, Jagiellonian University, ul. S. Łojasiewicza 11, 30-348 Kraków, Poland.
Entropy (Basel). 2018 Aug 31;20(9):658. doi: 10.3390/e20090658.
Scale free Lévy motion is a generalized analogue of the Wiener process. Its time derivative extends the notion of "white noise" to non-Gaussian noise sources, and as such, it has been widely used to model natural signal variations described by an overdamped Langevin stochastic differential equation. Here, we consider the dynamics of an archetypal model: a Brownian-like particle is driven by external forces, and noise is represented by uncorrelated Lévy fluctuations. An unperturbed system of that form eventually attains a steady state which is uniquely determined by the set of parameter values. We show that the analyzed Markov process with the stability index α < 2 violates the detailed balance, i.e., its stationary state is quantified by a stationary probability density and nonvanishing current. We discuss consequences of the non-Gibbsian character of the stationary state of the system and its impact on the general form of the fluctuation-dissipation theorem derived for weak external forcing.
无标度 Lévy 运动是维纳过程的一种广义类似物。它的时间导数将“白噪声”的概念扩展到非高斯噪声源,因此,它已被广泛用于对由过阻尼朗之万随机微分方程描述的自然信号变化进行建模。在这里,我们考虑一个典型模型的动力学:一个类似布朗运动的粒子受到外力驱动,噪声由不相关的 Lévy 涨落表示。这种形式的未受扰动系统最终会达到一个由参数值集唯一确定的稳态。我们表明,所分析的稳定性指数α < 2 的马尔可夫过程违反了细致平衡,即其稳态由一个稳态概率密度和非零电流来量化。我们讨论了系统稳态的非吉布斯特性的后果及其对为弱外部强迫推导的涨落耗散定理一般形式的影响。