Hodge Decomposition of Information Flow on Complex Networks

Yuuya Fujiki; Taichi Haruna

8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)

Research Article

Hodge Decomposition of Information Flow on Complex Networks

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/icst.bict.2014.257876,
    author={Yuuya Fujiki and Taichi Haruna},
    title={Hodge Decomposition of Information Flow on Complex Networks},
    proceedings={8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)},
    publisher={ICST},
    proceedings_a={BICT},
    year={2015},
    month={2},
    keywords={combinatorial hodge theory complex networks random threshold networks transfer entropy},
    doi={10.4108/icst.bict.2014.257876}
}

Yuuya Fujiki
Taichi Haruna
Year: 2015
Hodge Decomposition of Information Flow on Complex Networks
BICT
ACM
DOI: 10.4108/icst.bict.2014.257876

Yuuya Fujiki¹, Taichi Haruna¹^,*

1: Kobe University

*Contact email: tharuna@penguin.kobe-u.ac.jp

Abstract

Decomposition of information flow associated with random threshold network dynamics on random networks with specified degree distributions is studied by numerical simulation. Combinatorial Hodge theory enables us to orthogonally decompose information flow into gradient (unidirectional acyclic flow), harmonic (global circular flow) and curl (local circular flow) components. We show that in-degree distribution has little influence on the relative strength of the circular component (harmonic plus curl) while out-degree distributions with longer tail suppress it. We discuss an implication of this finding on the topology of real-world gene regulatory networks.

Keywords: combinatorial hodge theory complex networks random threshold networks transfer entropy

Published: 2015-02-02
Publisher: ICST
Appears in: ACM Digital Library

: http://dx.doi.org/10.4108/icst.bict.2014.257876