Generalized Dynamical Mean Field Theory for Non-Gaussian Interactions

We present a generalized dynamical mean field theory for studying the effects of non-Gaussian quenched noise in a general set of dynamical systems. We apply the framework to the generalized Lotka-Volterra equations, a central model in theoretical ecology, where species interactions are fixed over time and heterogeneous. Our results show that the new mean field equations have solutions that depend on all cumulants of the distribution of species interactions. We obtain an analytic solution when the interaction couplings are α-stable distributed and find a relationship between the abundance distribution of species and the statistics of microscopic interactions. In the case of sparse interactions, which we investigate analytically, we establish a simple relationship between the distribution of interactions and the one of population densities.

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Publication Details

Journal
Physical Review Letters
Published
2024-09-16
DOI
https://doi.org/10.1103/physrevlett.133.127401
Citations
12
Primary Topic
Statistical Mechanics and Entropy
Type
article
Field-Weighted Citation Impact
3.37

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article

Generalized Dynamical Mean Field Theory for Non-Gaussian Interactions

Sandro Azaele, Amos Maritan
12 citations
Physical Review Letters
Statistical Mechanics and Entropy
3.37
article

Generalized Dynamical Mean Field Theory for Non-Gaussian Interactions

Sandro Azaele, Amos Maritan
article en
12 citations

Abstract

We present a generalized dynamical mean field theory for studying the effects of non-Gaussian quenched noise in a general set of dynamical systems. We apply the framework to the generalized Lotka-Volterra equations, a central model in theoretical ecology, where species interactions are fixed over time and heterogeneous. Our results show that the new mean field equations have solutions that depend on all cumulants of the distribution of species interactions. We obtain an analytic solution when the interaction couplings are α-stable distributed and find a relationship between the abundance distribution of species and the statistics of microscopic interactions. In the case of sparse interactions, which we investigate analytically, we establish a simple relationship between the distribution of interactions and the one of population densities.

Physical Review LettersVol. 133(12)
University of Padua (IT), Istituto Nazionale di Fisica Nucleare, Sezione di Padova (IT), National Biodiversity Institute (CR)
European Commission
Openalex Percentile: Top 7%
Statistical Mechanics and Entropy
3.37
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