{"title":"自适应仓本模型的连续极限","authors":"Rok Cestnik, Erik A. Martens","doi":"arxiv-2407.03433","DOIUrl":null,"url":null,"abstract":"We investigate the dynamics of the adaptive Kuramoto model in the continuum\nlimit with slow adaptation. This model is distinguished by dense\nmultistability, where multiple states coexist for the same system parameters.\nThe underlying cause of this multistability is that some oscillators can lock\nat different phases or switch between locking and drifting depending on their\ninitial conditions. We identify new states, such as two-cluster states. To\nsimplify the analysis we introduce an approximate reduction of the model via\nrow-averaging of the coupling matrix. We derive a self-consistency equation for\nthe reduced model and present a stability diagram illustrating the effects of\npositive and negative adaptation. Our theoretical findings are validated\nthrough numerical simulations of a large finite system. Comparisons to previous\nwork highlight the significant influence of adaptation on synchronization\nbehavior.","PeriodicalId":501305,"journal":{"name":"arXiv - PHYS - Adaptation and Self-Organizing Systems","volume":"28 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Continuum limit of the adaptive Kuramoto model\",\"authors\":\"Rok Cestnik, Erik A. Martens\",\"doi\":\"arxiv-2407.03433\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We investigate the dynamics of the adaptive Kuramoto model in the continuum\\nlimit with slow adaptation. This model is distinguished by dense\\nmultistability, where multiple states coexist for the same system parameters.\\nThe underlying cause of this multistability is that some oscillators can lock\\nat different phases or switch between locking and drifting depending on their\\ninitial conditions. We identify new states, such as two-cluster states. To\\nsimplify the analysis we introduce an approximate reduction of the model via\\nrow-averaging of the coupling matrix. We derive a self-consistency equation for\\nthe reduced model and present a stability diagram illustrating the effects of\\npositive and negative adaptation. Our theoretical findings are validated\\nthrough numerical simulations of a large finite system. Comparisons to previous\\nwork highlight the significant influence of adaptation on synchronization\\nbehavior.\",\"PeriodicalId\":501305,\"journal\":{\"name\":\"arXiv - PHYS - Adaptation and Self-Organizing Systems\",\"volume\":\"28 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - PHYS - Adaptation and Self-Organizing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2407.03433\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Adaptation and Self-Organizing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.03433","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We investigate the dynamics of the adaptive Kuramoto model in the continuum
limit with slow adaptation. This model is distinguished by dense
multistability, where multiple states coexist for the same system parameters.
The underlying cause of this multistability is that some oscillators can lock
at different phases or switch between locking and drifting depending on their
initial conditions. We identify new states, such as two-cluster states. To
simplify the analysis we introduce an approximate reduction of the model via
row-averaging of the coupling matrix. We derive a self-consistency equation for
the reduced model and present a stability diagram illustrating the effects of
positive and negative adaptation. Our theoretical findings are validated
through numerical simulations of a large finite system. Comparisons to previous
work highlight the significant influence of adaptation on synchronization
behavior.