dorsal/arxiv
View SchemaHeterogeneous animal group models and their group-level alignment dynamics; an equation-free approach
| Authors | Sung Joon Moon, B. Nabet, Naomi E. Leonard, Simon A. Levin, I. G. Kevrekidis |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0606021 |
| URL | https://arxiv.org/abs/q-bio/0606021 |
Abstract
We study coarse-grained (group-level) alignment dynamics of individual-based animal group models for {\it heterogeneous} populations consisting of informed (on preferred directions) and uninformed individuals. The orientation of each individual is characterized by an angle, whose dynamics are nonlinearly coupled with those of all the other individuals, with an explicit dependence on the difference between the individual's orientation and the instantaneous average direction. Choosing convenient coarse-grained variables (suggested by uncertainty quantification methods) that account for rapidly developing correlations during initial transients, we perform efficient computations of coarse-grained steady states and their bifurcation analysis. We circumvent the derivation of coarse-grained governing equations, following an equation-free computational approach.
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"date_created": "2026-03-02T18:01:35.763000Z",
"date_modified": "2026-03-02T18:01:35.763000Z",
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"abstract": "We study coarse-grained (group-level) alignment dynamics of individual-based\nanimal group models for {\\it heterogeneous} populations consisting of informed\n(on preferred directions) and uninformed individuals. The orientation of each\nindividual is characterized by an angle, whose dynamics are nonlinearly coupled\nwith those of all the other individuals, with an explicit dependence on the\ndifference between the individual\u0027s orientation and the instantaneous average\ndirection. Choosing convenient coarse-grained variables (suggested by\nuncertainty quantification methods) that account for rapidly developing\ncorrelations during initial transients, we perform efficient computations of\ncoarse-grained steady states and their bifurcation analysis. We circumvent the\nderivation of coarse-grained governing equations, following an equation-free\ncomputational approach.",
"arxiv_id": "q-bio/0606021",
"authors": [
"Sung Joon Moon",
"B. Nabet",
"Naomi E. Leonard",
"Simon A. Levin",
"I. G. Kevrekidis"
],
"categories": [
"q-bio.QM",
"q-bio.PE"
],
"title": "Heterogeneous animal group models and their group-level alignment dynamics; an equation-free approach",
"url": "https://arxiv.org/abs/q-bio/0606021"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "dd7998ce-85b0-448e-b1af-10452a0d1868",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
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"user_id": 1000002
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