Transition to synchronization in adaptive Sakaguchi-Kuramoto model with higher-order interactions
Sangita Dutta, Prosenjit Kundu, Pitambar Khanra, Chittaranjan Hens,, Pinaki Pal

TL;DR
This paper explores how synchronization transitions occur in an adaptive Sakaguchi-Kuramoto model with higher-order interactions, revealing both continuous and discontinuous transitions through simulations and reduced modeling.
Contribution
It introduces a reduced order model based on the Ott-Antonsen ansatz to analytically understand complex synchronization transitions in the system.
Findings
Continuous transition linked to supercritical pitchfork bifurcation.
Discontinuous tiered transition involves multiple saddle-node bifurcations.
Explosive transition associated with subcritical pitchfork and saddle-node bifurcations.
Abstract
We investigate the phenomenon of transition to synchronization in Sakaguchi-Kuramoto model in the presence of higher-order interactions and global order parameter adaptation. The investigation is done by performing extensive numerical simulations and low dimensional modeling of the system. Numerical simulations of the full system show both continuous (second order) as well as discontinuous transitions. The discontinuous transitions can either be associated with explosive (first order) or with tiered synchronization states depending on the choice of parameters. To develop an in depth understanding of the transition scenario in the parameter space we derive a reduced order model (ROM) using the Ott-Antonsen ansatz, the results of which closely matches with that of the numerical simulations of the full system. The simplicity and analytical accessibility of the ROM helps to conveniently…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNonlinear Dynamics and Pattern Formation · Opinion Dynamics and Social Influence
