$N$-dependent Multiplicative-Noise Contributions in Finite $N$-unit Langevin Models: Augmented Moment Approach

TL;DR

This paper extends the augmented moment method to analyze finite N-unit Langevin models with additive and multiplicative noises, revealing that multiplicative noise does not scale simply with 1/√N, contrary to naive assumptions, and matches simulation results.

Contribution

The paper introduces an improved analysis of N-unit Langevin models showing the non-trivial scaling of multiplicative noise, enhancing understanding of stochastic dynamics in such systems.

Findings

AMM results agree with direct simulations

Additive noise scales as 1/√N, but multiplicative noise does not

Naive scaling assumptions violate the central-limit theorem

Abstract

Finite $N$-unit Langevin models with additive and multiplicative noises have been studied with the use of the augmented moment method (AMM) previously proposed by the author [H. Hasegawa, Phys. Rev E {\bf 67}, 041903 (2003)]. Original $N$-dimensional stochastic equations are transformed to the three-dimensional deterministic equations for means and fluctuations of local and global variables. Calculated results of our AMM are in good agreement with those of direct simulations (DS). We have shown that although the effective strength of the additive noise of the $N$-unit system is scaled as $\beta(N)=\beta(1)/\sqrt{N}$, it is not the case for multiplicative noise [$\alpha(N) \neq \alpha(1)/\sqrt{N}$], where $\alpha(N)$ and $\beta(N)$ denote the strength of multiplicative and additive noises, respectively, for the size-$N$ system. It has been pointed out that the naive assumption of $\alpha(N) = \alpha(1)/\sqrt{N}$ leads to result which violates the central-limit theorem and which does not agree with those of DS and AMM.