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A nonlocal-to-local approach to aggregation-diffusion equations

Abstract:
Over the past few decades, nonlocal models have been widely used to describe aggregation phenomena in biology, physics, engineering, and the social sciences. These are often derived as mean-field limits of attraction-repulsion agent-based models and consist of systems of nonlocal partial differential equations. Using differential adhesion between cells as a biological case study, we introduce a novel local model of aggregation-diffusion phenomena. This system of local aggregation-diffusion equations is fourth-order, resembling thin-film or Cahn–Hilliard type equations. In this framework, cell sorting phenomena are explained through relative surface tensions between distinct cell types. The local model emerges as a limiting case of short-range interactions, providing a significant simplification of earlier nonlocal models while preserving the same phenomenology. This simplification makes the model easier to implement numerically and more amenable to calibration to quantitative data. In addition, we discuss recent analytical results based on the gradient flow structure of the model, along with open problems and future research directions.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1137/25m1726248

Authors

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Role:
Author
ORCID:
0000-0001-9832-2697
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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Oxford college:
St Hugh's College
Role:
Author
ORCID:
0000-0002-6304-9333
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author


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Funder identifier:
https://ror.org/0472cxd90
Grant:
883363
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Funder identifier:
https://ror.org/0439y7842
Grant:
EP/V051121/1
EP/T022132/1


Publisher:
Society for Industrial and Applied Mathematics
Journal:
SIAM Review More from this journal
Volume:
67
Issue:
2
Pages:
353-372
Publication date:
2025-05-08
Acceptance date:
2025-01-15
DOI:
EISSN:
1095-7200
ISSN:
0036-1445


Language:
English
Keywords:
Pubs id:
2123242
Local pid:
pubs:2123242
Deposit date:
2025-05-12
ARK identifier:

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