| Autor: |
Yadav A; School of Physics, Indian Institute of Science Education and Research Thiruvananthapuram, Kerala 695551, India., J K; School of Physics, Indian Institute of Science Education and Research Thiruvananthapuram, Kerala 695551, India., Chandrasekar VK; Center for Nonlinear Science and Engineering, SASTRA Deemed University, Thanjavur, Tamil Nadu 613401, India., Zou W; School of Mathematical Sciences, South China Normal University, Guangzhou 510631, China., Kurths J; Potsdam Institute for Climate Impact Research, Telegraphenberg, D-14415 Potsdam, Germany.; Institute of Physics, Humboldt University Berlin, D-12489 Berlin, Germany.; Research Institute of Intelligent Complex Systems, Fudan University, Shanghai 200433, China., Senthilkumar DV; School of Physics, Indian Institute of Science Education and Research Thiruvananthapuram, Kerala 695551, India. |
| Abstrakt: |
Swarmalators are oscillators that can swarm as well as sync via a dynamic balance between their spatial proximity and phase similarity. Swarmalator models employed so far in the literature comprise only one-dimensional phase variables to represent the intrinsic dynamics of the natural collectives. Nevertheless, the latter can indeed be represented more realistically by high-dimensional phase variables. For instance, the alignment of velocity vectors in a school of fish or a flock of birds can be more realistically set up in three-dimensional space, while the alignment of opinion formation in population dynamics could be multidimensional, in general. We present a generalized D-dimensional swarmalator model, which more accurately captures self-organizing behaviors of a plethora of real-world collectives by self-adaptation of high-dimensional spatial and phase variables. For a more sensible visualization and interpretation of the results, we restrict our simulations to three-dimensional spatial and phase variables. Our model provides a framework for modeling complicated processes such as flocking, schooling of fish, cell sorting during embryonic development, residential segregation, and opinion dynamics in social groups. We demonstrate its versatility by capturing the maneuvers of a school of fish, qualitatively and quantitatively, by a suitable extension of the original model to incorporate appropriate features besides a gallery of its intrinsic self-organizations for various interactions. We expect the proposed high-dimensional swarmalator model to be potentially useful in describing swarming systems and programmable and reconfigurable collectives in a wide range of disciplines, including the physics of active matter, developmental biology, sociology, and engineering. |
