Stochastic equation for a jumping process with long-time correlations
T. Srokowski, A. Kaminska
Abstract
A jumping process, defined in terms of jump size distribution and waiting time distribution, is presented. The jumping rate depends on the process value. The process, which is Markovian and stationary, relaxes to an equilibrium and is characterized by the power-law autocorrelation function. Therefore, it can serve as a model of the 1/f noise as well as a model of the stochastic force in the generalized Langevin equation. This equation is solved for the noise correlations 1/t; the resulting velocity distribution has sharply falling tails. The system preserves the memory about the initial condition for a very long time.
Create a lesson
Related papers
Dynamically Reentrant Skyrmion Phase in Oscillating Magnetic Fields
Z. Demir Vatansever, E. Vatansever, A. Vasilopoulos et al.
Mutual linearity in semi-Markov networks
Julian B. Voits, Ulrich S. Schwarz
Steady states in asymmetric exclusion processes with reactions: Fluctuations and non-mean field behaviour
Rohn Chatterjee, Atri Goswami, Sudip Mukherjee
Marginal Operator Deformations and Pseudocriticality in Baxter--Wu Models
Hyun-Yong Lee, Naoki Kawashima, Nikolaos G. Fytas et al.
Kardar--Parisi--Zhang density hydrodynamics in a coherent XXZ--ASEP Lindbladian
Yansheng Liu, Daoguang Li, Kaixiang Lu et al.
Brownian gyrator model with stochastic resetting
Satya N. Majumdar, Gregory Schehr, Pascal Viot et al.