Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Gkogkas, Marios Antonios"'
Publikováno v:
Chaos 2022
Models of coupled oscillator networks play an important role in describing collective synchronization dynamics in biological and technological systems. The Kuramoto model describes oscillator's phase evolution and explains the transition from incoher
Externí odkaz:
http://arxiv.org/abs/2203.16839
Many science phenomena are modelled as interacting particle systems (IPS) coupled on static networks. In reality, network connections are far more dynamic. Connections among individuals receive feedback from nearby individuals and make changes to bet
Externí odkaz:
http://arxiv.org/abs/2202.01742
Adaptive (or co-evolutionary) network dynamics, i.e., when changes of the network/graph topology are coupled with changes in the node/vertex dynamics, can give rise to rich and complex dynamical behavior. Even though adaptivity can improve the modell
Externí odkaz:
http://arxiv.org/abs/2109.05898
Originally arising in the context of interacting particle systems in statistical physics, dynamical systems and differential equations on networks/graphs have permeated into a broad number of mathematical areas as well as into many applications. One
Externí odkaz:
http://arxiv.org/abs/2007.02868
Homogenization of Fully-Coupled Chaotic Fast-Slow Systems via Intermediate Stochastic Regularization
In this paper we study coupled fast-slow ordinary differential equations (ODEs) with small time scale separation parameter $\epsilon$ such that, for every fixed value of the slow variable, the fast dynamics are sufficiently chaotic with ergodic invar
Externí odkaz:
http://arxiv.org/abs/2003.11297
Publikováno v:
Communications in Mathematical Sciences. 21:83-106
Adaptive (or co-evolutionary) network dynamics, i.e., when changes of the network/graph topology are coupled with changes in the node/vertex dynamics, can give rise to rich and complex dynamical behavior. Even though adaptivity can improve the modell
Autor:
Engel, Maximilian1 (AUTHOR), Gkogkas, Marios Antonios2 (AUTHOR) marios.gkogkas@yahoo.de, Kuehn, Christian2 (AUTHOR)
Publikováno v:
Journal of Statistical Physics. May2021, Vol. 183 Issue 2, p1-34. 34p.
Akademický článek
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