A unifying framework for mean-field theories of asymmetric kinetic Ising systems.pdf (1.04 MB)
A unifying framework for mean-field theories of asymmetric kinetic Ising systems
journal contribution
posted on 2023-06-09, 23:32 authored by Miguel Aguilera, S Amin Moosavi, Hideaki ShimazakiKinetic 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 develop novel methods that, in contrast with traditional approaches, preserve the system’s correlations. We show that these new methods can outperform previous ones in predicting and assessing network properties near maximally fluctuating regimes.
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Publication status
- Published
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- Published version
Journal
Nature CommunicationsISSN
2041-1723Publisher
Nature ResearchExternal DOI
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12Page range
1-12Article number
a1197Event location
EnglandDepartment affiliated with
- Informatics Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2021-04-12First Open Access (FOA) Date
2021-04-12First Compliant Deposit (FCD) Date
2021-04-09Usage metrics
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