A unifying framework for mean-field theories of asymmetric kinetic Ising systems.

ABSTRACT: Kinetic Ising models are powerful tools for studying the non-equilibrium dynamics of complex systems. As their behavior is not tractable for large networks, many mean-field methods have been proposed for their analysis, each based on unique assumptions about the system's temporal evolution. This disparity of approaches makes it challenging to systematically advance mean-field methods beyond previous contributions. Here, we propose a unifying framework for mean-field theories of asymmetric kinetic Ising systems from an information geometry perspective. The framework is built on Plefka expansions of a system around a simplified model obtained by an orthogonal projection to a sub-manifold of tractable probability distributions. This view not only unifies previous methods but also allows us to

SUBMITTER: Aguilera M 

PROVIDER: S-EPMC7895831 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature