Information Propagation in Predator-Prey Dynamics of Turbulent Plasma

TL;DR

This paper models predator-prey interactions in turbulent plasma using a stochastic approach, revealing that intrinsic noise causes persistent quasi-cycles and that zonal flow information influences turbulence, with implications for predictability.

Contribution

It introduces a stochastic predator-prey model for plasma turbulence and demonstrates how intrinsic fluctuations lead to quasi-cycles and information transfer from zonal flow to turbulence.

Findings

Intrinsic noise causes persistent quasi-cycles in the model.

Zonal flow information propagates to turbulence.

Periodic oscillations may be quasi-cycles rather than limit cycles.

Abstract

Magnetically confined fusion plasmas exhibit predator-prey-like cyclic oscillations through the self-regulating interaction between drift-wave turbulence and zonal flow. To elucidate the detailed mechanism and causality underlying this phenomenon, we construct a simple stochastic predator-prey model that incorporates intrinsic fluctuations and analyze its statistical properties from an information-theoretic perspective. We first show that the model exhibits persistent fluctuating cyclic oscillations called quasi-cycles due to amplification of intrinsic noise. This result suggests the possibility that the previously observed periodic oscillations in a toroidal plasma are not limit cycles but quasi-cycles, and that such quasi-cycles may be widely observed under various conditions. For this model, we further prove that information of the zonal flow is propagated to turbulence. This result suggests that turbulence behavior may be predictable to a certain extent based on zonal flow characteristics.