Graphop Mean-Field Limits and Synchronization for the Stochastic Kuramoto Model

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Hauptverfasser: Gkogkas, Marios Antonios, Jüttner, Benjamin, Kuehn, Christian, Martens, Erik Andreas
Format: Preprint
Veröffentlicht: 2022
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author Gkogkas, Marios Antonios
Jüttner, Benjamin
Kuehn, Christian
Martens, Erik Andreas
author_facet Gkogkas, Marios Antonios
Jüttner, Benjamin
Kuehn, Christian
Martens, Erik Andreas
contents 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 incoherent to coherent oscillations under simplifying assumptions including all-to-all coupling with uniform strength. Real world networks, however, often display heterogeneous connectivity and coupling weights that influence the critical threshold for this transition. We formulate a general mean field theory (Vlasov-Focker Planck equation) for stochastic Kuramoto-type phase oscillator models, valid for coupling graphs/networks with heterogeneous connectivity and coupling strengths, using graphop theory in the mean field limit. Considering symmetric odd-valued coupling functions, we mathematically prove an exact formula for the critical threshold for the incoherence-coherence transition. We numerically test the predicted threshold using large finite-size representations of the network model. For a large class of graph models, we find that the numerical tests agree very well with the predicted threshold obtained from mean field theory. However, the prediction is more difficult in practice for graph structures that are sufficiently sparse. Our findings open future research avenues toward a deeper understanding of mean-field theories for heterogeneous systems.
format Preprint
id arxiv_https___arxiv_org_abs_2203_16839
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Graphop Mean-Field Limits and Synchronization for the Stochastic Kuramoto Model
Gkogkas, Marios Antonios
Jüttner, Benjamin
Kuehn, Christian
Martens, Erik Andreas
Adaptation and Self-Organizing Systems
Dynamical Systems
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 incoherent to coherent oscillations under simplifying assumptions including all-to-all coupling with uniform strength. Real world networks, however, often display heterogeneous connectivity and coupling weights that influence the critical threshold for this transition. We formulate a general mean field theory (Vlasov-Focker Planck equation) for stochastic Kuramoto-type phase oscillator models, valid for coupling graphs/networks with heterogeneous connectivity and coupling strengths, using graphop theory in the mean field limit. Considering symmetric odd-valued coupling functions, we mathematically prove an exact formula for the critical threshold for the incoherence-coherence transition. We numerically test the predicted threshold using large finite-size representations of the network model. For a large class of graph models, we find that the numerical tests agree very well with the predicted threshold obtained from mean field theory. However, the prediction is more difficult in practice for graph structures that are sufficiently sparse. Our findings open future research avenues toward a deeper understanding of mean-field theories for heterogeneous systems.
title Graphop Mean-Field Limits and Synchronization for the Stochastic Kuramoto Model
topic Adaptation and Self-Organizing Systems
Dynamical Systems
url https://arxiv.org/abs/2203.16839