Affiliation:
1. Departamento de Física, Universidade Federal do Ceará, Fortaleza, Ceará 60451-970, Brazil
2. Levich Institute and Physics Department, The City College of New York, New York, New York 10031, USA
Abstract
Recent studies have revealed the interplay between the structure of network circuits with fibration symmetries and the functionality of biological networks within which they have been identified. The presence of these symmetries in complex networks predicts the phenomenon of cluster synchronization, which produces patterns of a synchronized group of nodes. Here, we present a fast, and memory efficient, algorithm to identify fibration symmetries in networks. The algorithm is particularly suitable for large networks since it has a runtime of complexity [Formula: see text] and requires [Formula: see text] of memory resources, where [Formula: see text] and [Formula: see text] are the number of nodes and edges in the network, respectively. The algorithm is a modification of the so-called refinement paradigm to identify circuits that are symmetrical to information flow (i.e., fibers) by finding the coarsest refinement partition over the network. Finally, we show that the algorithm provides an optimal procedure for identifying fibers, overcoming current approaches used in the literature.
Funder
National Institutes of Health
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico
Instituto Nacional de Ciência e Tecnologia de Sistemas Complexos
Subject
Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics
Cited by
2 articles.
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