Multiplexing-based control of wavefront propagation: the interplay of inter-layer coupling, asymmetry and noise
arXiv:2305.00759 · doi:10.1016/j.chaos.2023.113656
Abstract
We show how multiplexing influences propagating fronts in multilayer networks of coupled bistable oscillators. Using numerical simulation, we investigate both deterministic and noise-sustained propagation. In particular, we demonstrate that the multiplexing allows to reduce the intra-layer dynamics to a common regime where the front propagation speed in all the interacting layers attains the same fixed value. In the presence of noise the dynamics is more complicated and is characterized by the ability of the system to adjust to the common propagation speed for varying the multiplexing strength. In addition, we find that the noise-induced stabilization of wavefront propagation in multilayer networks allows to obtain less pronounced deviations of the wavefront compared to the stabilization achieved in the isolated layer. Finally, we demonstrate that the reduction of the wavefront deviations can be enhanced by increasing the number of interacting layers.
arXiv comment7 pages, 4 figures
References in corpus (20)
- Theory of Phase Ordering Kinetics
- Stochastic population dynamics in spatially extended predator-prey systems
- Dynamics of Random Neural Networks with Bistable Units
- Weak multiplexing in neural networks: Switching between chimera and solitary states
- Intrinsic noise-induced phase transitions: beyond the noise interpretation
- Coherence resonance in a network of FitzHugh-Nagumo systems: interplay of noise, time-delay and topology
- Understanding and mitigating noise in trained deep neural networks
- Topics in coarsening phenomena
- Control of coherence resonance in multiplex neural networks
- Fundamental aspects of noise in analog-hardware neural networks
- Coherence resonance in neuronal populations: mean-field versus network model
- Arrest of Domain Coarsening via Antiperiodic Regimes in Delay Systems
- Solitary states in multiplex neural networks: onset and vulnerability
- A bio-inspired bistable recurrent cell allows for long-lasting memory
- Asymmetry-induced order in multilayer networks
- Dissipative solitons for bistable delayed-feedback systems
- Multiplexing-based control of stochastic resonance
- Topology Controlled Potts Coarsening
- Ising model with memory: coarsening and persistence properties
- Coarsening Dynamics of Granular Heaplets in Tapped Granular Layers