
Uniform stability and uniform-in-time mean-field limit of the thermodynamic Kuramoto model
Author(s) -
SeungYeal Ha,
Myeongju Kang,
Hansol Park,
Tommaso Ruggeri,
Woojoo Shim
Publication year - 2021
Publication title -
quarterly of applied mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.603
H-Index - 41
eISSN - 1552-4485
pISSN - 0033-569X
DOI - 10.1090/qam/1588
Subject(s) - stability (learning theory) , algorithm , limit (mathematics) , field (mathematics) , mathematics , computer science , machine learning , mathematical analysis , pure mathematics
We consider the thermodynamic Kuramoto model proposed in \cite{H-P-R-S}. For each oscillator in thermodynamic Kuramoto model, there is a coupling effect between the phase and the temperature field. For such a model, we study a uniform stability and uniform-in-time mean-field limit to the corresponding kinetic equation. For this, we first derive a uniform ℓ p \ell ^p -stability of the thermodynamic Kuramoto model with respect to initial data by directly estimating the temporal evolution of ℓ p \ell ^p -distance between two admissible solutions to the particle thermodynamic Kuramoto model. In a large-oscillator limit, the Vlasov type mean-field equation can be rigorously derived using the BBGKY hierarchy, uniform stability estimate, and particle-in-cell method. We construct unique global-in-time measure-valued solutions to the derived kinetic equation and also derive a uniform-in-time stability estimate and emergent estimates.