# gst: time-delayed dynamics in regular Kuramoto networks with inertia: multistability, traveling waves, chimera states, and transitions to seizure-like activity.

<< ️This (AA) study examines the complex interplay between inertia and time delay in regular rotor networks within the framework of the second-order Kuramoto model. By combining analytical and numerical methods, (AA) demonstrate that intrinsic time delays -- arising from finite information transmission speeds - induce multistability among fully synchronized phase-locked states. >>

<< ️Unlike systems without inertia, the presence of inertia destabilizes these phase-locked states, reduces their basin of attraction, and gives rise to nonlinear phase-locked dynamics over specific inertia ranges. >>

<< ️In addition, (They) show that time delays promote the emergence of turbulent chimera states, while inertia enhances their spatial extent. Notably, the combined influence of inertia and time delay produces dynamic patterns reminiscent of partial epileptic seizures. >>

Esmaeil Mahdavi, Mina Zarei, Philipp Hövel, Farhad Shahbazi. Time-Delayed Dynamics in Regular Kuramoto Networks with Inertia: Multistability, Traveling Waves, Chimera States, and Transitions to Seizure-Like Activity.  arXiv: 2512.16640v1 [nlin.AO]. Dec 18, 2025.

https://arxiv.org/abs/2512.16640

Also: network, transition, waves, chimera, turbulence, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, networks, transitions, waves, chimera, turbulence, inertia, time delay, multistability, epileptic seizures.

# gst: chimera states in wheel networks

<< ️How higher-order interactions influence dynamical behavior in networks of coupled chaotic oscillators remains an open question. To address this, (AA) investigate emergent dynamical behaviors in a wheel network of Rössler and Lorenz oscillators that incorporates both pairwise (1-simplex) and higher-order (2-simplex) interactions under three coupling schemes, namely, diffusive, conjugate, and mean-field diffusive coupling. >>

<< ️(AA) numerical analysis reveals four distinct collective behaviors: synchronization, desynchronization, chimera states, and synchronized clusters. To systematically classify these dynamical behaviors, (They) introduce two statistical measures that effectively capture synchronization patterns among arbitrarily positioned nodes. Applying these measures across all dynamical models and coupling schemes (six different models in total), (They) show that both pairwise and higher-order interactions crucially influence the emergence and robustness of chimera states. (They) observe that under pairwise interaction alone, chimera states appear with high prevalence in specific coupling ranges, though the robustness depends on both the coupling scheme and the underlying dynamical system. >>

<< Incorporation of higher-order interactions reveals that the higher-order interaction underlying diffusive coupling enhances chimera states in both Rössler and Lorenz networks; under conjugate coupling, it strengthens chimera states in Lorenz but instead promotes full synchronization in Rössler; and under mean-field diffusive coupling, higher-order interactions generally favor synchronization, particularly for Rössler oscillators, but promote chimera in the Lorenz system for the intermediate range of its strengths. >>

<< ️Overall, (AA) results demonstrate that higher-order interactions can significantly modulate, promote, or suppress chimera states depending on the coupling mechanism and oscillator dynamics. >>

Ashwathi Poolamanna, Medha Bhindwar, Chandrakala Meena. Chimera States in Wheel Networks. arXiv: 2601.01411v1 [nlin.CD]. Jan 4, 2026.

https://arxiv.org/abs/2601.01411

Also: chimera, network, transition, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, chimera, network, transitions

# gst: finding information in the randomness of living matter.

<< ️In recent research, (AA) succeeded in developing a theoretical description that can rigorously characterize the role of fluctuations in systems. "It is mathematically challenging to predict the behavior of such systems if using traditional tools from statistical mechanics," (Martin Kjøllesdal Johnsrud) >>.

<< ️The physicists thus developed a suitable mathematical tool to extend the existing field theories, and they are now able to make predictions about systems out of equilibrium, such as active matter. "With our formalism, we are able to define measurable quantities that can help to characterize nonequilibrium dynamics of living matter and enable experimental design of artificial active systems," (Ramin Golestanian) >>. 

Manuel Maidorn. Finding information in the randomness of living matter. Phys.org. Nov 28, 2025.

https://phys.org/news/2025-11-randomness.html

Martin Kjøllesdal Johnsrud, Ramin Golestanian. Phys. Rev. Research 7, L032053. Sep 9, 2025.

https://journals.aps.org/prresearch/abstract/10.1103/xx4z-lj5c

Martin Kjøllesdal Johnsrud, Ramin Golestanian. Phys. Rev. Research 7, L032054. Sep 9, 2025.

https://journals.aps.org/prresearch/abstract/10.1103/flzv-lq7x

Also: gst, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, active matter, complex systems, microscopic fluctuations, noise, nonequilibrium dynamics, stochastic field theories, statistical mechanics.

# gst: apropos of itinerant behaviors, from chaotic itinerancy to intermittent synchronization in complex networks.

<< ️Although synchronization has been extensively studied, important processes underlying its emergence have remained hidden by the use of global order parameters. Here, (AA) uncover how the route unfolds through a sequential transition between two well-known but previously unconnected phenomena: chaotic itinerancy (CI) and intermittent synchronization (IS). >>

<< ️Using a new symbolic dynamics, (They) show that CI emerges as a collective yet unsynchronized exploration of different domains of the high-dimensional attractor, whose dimension is reduced as the coupling increases, ultimately collapsing back into the reference chaotic attractor of an individual unit. At this stage, the IS can emerge as irregular alternations between synchronous and asynchronous phases. The two phenomena are therefore mutually exclusive, each dominating a distinct coupling interval and governed by different mechanisms. >>

<< ️Network structural heterogeneity enhances itinerant behavior since access to different domains of the attractor depends on the nodes' topological roles. The CI--IS crossover occurs within a consistent coupling interval across models and topologies. Experiments on electronic oscillator networks confirm this two-step process, establishing a unified framework for the route to synchronization in complex systems. >>

I. Leyva, Irene Sendiña-Nadal, Christophe Letellier, et al. From chaotic itinerancy to intermittent synchronization in complex networks. arXiv: 2511.09253v1 [nlin.AO]. Nov 12, 2025.

https://arxiv.org/abs/2511.09253

Also: network, behav, intermittency, transition, attractor, chaos, collapse, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, networks, behavior, intermittency, transitions, attractor, chaos, collapse, chaotic itinerancy, intermittent synchronization, structural heterogeneity, itinerant behavior.