Saved in:
Bibliographic Details
Main Authors: Shivamoggi, Bhimsen, Tuovila, Nicole
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2412.02820
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866910787564470272
author Shivamoggi, Bhimsen
Tuovila, Nicole
author_facet Shivamoggi, Bhimsen
Tuovila, Nicole
contents The purpose of this paper is to consider the application of the direct interaction approximation (DIA) developed by Kraichnan to generalized stochastic models in the turbulence problem. Previous developments were based on the Boltzmann-Gibbs prescription for the underlying entropy measure, which exhibits the extensivity property and is suited for ergodic systems. Here, we consider the introduction of an influence bias discriminating rare and frequent events explicitly, as it behooves non-ergodic systems, which is dealt with by a using a Tsallis type autocorrelation model with an underlying non-extensive entropy measure. As an example, we consider a linear damped stochastic oscillator system, and describe the resulting stochastic process. The non-perturbative aspects excluded by Keller's perturbative procedure are found to be minimized in the white-noise limit. In the opposite limit, the physical variances between the random process models don't seem to materialize, and the Uhlenbeck-Ornstein and Tsallis type models are found to yield the same result. In the process, we also deduce some apparently novel mathematical properties of the stochastic models associated with the present investigation -- the gamma distribution and the Tsallis non-extensive entropy.
format Preprint
id arxiv_https___arxiv_org_abs_2412_02820
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Direct Interaction Approximation for generalized stochastic models in the turbulence problem
Shivamoggi, Bhimsen
Tuovila, Nicole
Mathematical Physics
The purpose of this paper is to consider the application of the direct interaction approximation (DIA) developed by Kraichnan to generalized stochastic models in the turbulence problem. Previous developments were based on the Boltzmann-Gibbs prescription for the underlying entropy measure, which exhibits the extensivity property and is suited for ergodic systems. Here, we consider the introduction of an influence bias discriminating rare and frequent events explicitly, as it behooves non-ergodic systems, which is dealt with by a using a Tsallis type autocorrelation model with an underlying non-extensive entropy measure. As an example, we consider a linear damped stochastic oscillator system, and describe the resulting stochastic process. The non-perturbative aspects excluded by Keller's perturbative procedure are found to be minimized in the white-noise limit. In the opposite limit, the physical variances between the random process models don't seem to materialize, and the Uhlenbeck-Ornstein and Tsallis type models are found to yield the same result. In the process, we also deduce some apparently novel mathematical properties of the stochastic models associated with the present investigation -- the gamma distribution and the Tsallis non-extensive entropy.
title Direct Interaction Approximation for generalized stochastic models in the turbulence problem
topic Mathematical Physics
url https://arxiv.org/abs/2412.02820