Investigation on the properties of sineWiener noise and its induced escape in the particular limit case D → ∞
Abstract
SineWiener (SW) noise is increasingly adopted in realistic stochastic modeling for its bounded nature. However, many features of the SW noise are still unexplored. In this paper, firstly, the properties of the SW noise and its integral process are explored as the parameter D in the SW noise tends to be infinite. It is found that although the distribution of the SW noise is quite different from Gaussian white noise, the integral process of the SW noise shows many similarities with the Wiener process. Inspired by the Wiener process, which uses the diffusion coefficient to denote the intensity of the Gaussian noise, a quantity is put forward to characterize the SW noise's intensity. Then we apply the SW noise to a onedimensional doublewell potential system and the MaierStein system to investigate the escape behaviors. A more interesting result is observed that the mean first exit time also follows the wellknown Arrhenius law as in the case of the Gaussian noise, and the quasipotential and the exit location distributions are very close to the results of the Gaussian noise.
 Publication:

Journal of Statistical Mechanics: Theory and Experiment
 Pub Date:
 October 2021
 DOI:
 10.1088/17425468/ac2a9f
 arXiv:
 arXiv:2107.09641
 Bibcode:
 2021JSMTE2021j3211W
 Keywords:

 diffusion;
 fluctuation theorem;
 large deviation;
 stochastic processes;
 Condensed Matter  Statistical Mechanics;
 Physics  Data Analysis;
 Statistics and Probability
 EPrint:
 13 pages, 8 figures, 3 tables