The paper establishes sharp relative entropy estimates for marginals of non-exchangeable interacting particle systems by linking a BBGKY hierarchy to first-passage percolation.
The mean field analysis for the Kuramoto model on graphs I. The mean field equation and transition point formulas
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
In his classical work on synchronization, Kuramoto derived the formula for the critical value of the coupling strength corresponding to the transition to synchrony in large ensembles of all-to-all coupled phase oscillators with randomly distributed intrinsic frequencies. We extend the Kuramoto's result to a large class of coupled systems on convergent families of deterministic and random graphs. Specifically, we identify the critical values of the coupling strength (transition points), between which the incoherent state is linearly stable and is unstable otherwise. We show that the transition points depend on the largest positive or/and smallest negative eigenvalue(s) of the kernel operator defined by the graph limit. This reveals the precise mechanism, by which the network topology controls transition to synchrony in the Kuramoto model on graphs. To illustrate the analysis with concrete examples, we derive the transition point formula for the coupled systems on Erd\H{o}s-R\'{e}nyi, small-world, and $k$-nearest-neighbor families of graphs. As a result of independent interest, we provide a rigorous justification for the mean field limit for the Kuramoto model on graphs. The latter is used in the derivation of the transition point formulas.
fields
math.PR 1years
2024 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Quantitative propagation of chaos for non-exchangeable diffusions via first-passage percolation
The paper establishes sharp relative entropy estimates for marginals of non-exchangeable interacting particle systems by linking a BBGKY hierarchy to first-passage percolation.