Collective excitability in highly diluted random networks of oscillators

Year: 2022

Authors: Paolini G., Ciszak M., Marino F., Olmi S., Torcini A.

Autors Affiliation: CY Cergy Paris Univ, Lab Phys Theor & Modelisat, CNRS, UMR 8089, F-95302 Cergy Pontoise, France; CNR, Ist Nazl Ott, via Sansone 1, I-50019 Sesto Fiorentino, Italy; INFN, Sez Firenze, I-50019 Sesto Fiorentino, Italy; CNR, Ist Sistemi Complessi, via Madonna Piano 10, I-50019 Sesto Fiorentino, Italy.

Abstract: We report on collective excitable events in a highly diluted random network of non-excitable nodes. Excitability arises thanks to a self-sustained local adaptation mechanism that drives the system on a slow timescale across a hysteretic phase transition involving states with different degrees of synchronization. These phenomena have been investigated for the Kuramoto model with bimodal distribution of the natural frequencies and for the Kuramoto model with inertia and a unimodal frequency distribution. We consider global and partial stimulation protocols and characterize the system response for different levels of dilution. We compare the results with those obtained in the fully coupled case showing that such collective phenomena are remarkably robust against network diluteness.

Journal/Review: CHAOS

Volume: 32 (10)      Pages from: 103108-1  to: 103108-12

More Information: A.T. received financial support from the Labex MME-DII (Grant No. ANR-11-LBX-0023-01) (together with MP) and from the ANR Project ERMUNDY (Grant No. ANR-18-CE37-0014), all part of the French program “Investissements dŽAvenir.” Part of this work has been developed during the visit of SO during 2021 to the Maison internationale de La Recherche, Neuville-sur-Oise, France supported by CY Advanced Studies, CY Cergy Paris Universite, France.
KeyWords: Statistical analysis, Complex adaptive systems, Phase transitions,
Canard, Kuramoto models, Chaos synchronization

DOI: 10.1063/5.0102880

Citations: 2
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