A Nonlinear Model for Long-Range Segregation

We study a system of fully nonlinear elliptic equations, depending on a small parameter $$\varepsilon $$ , that models long-range segregation of populations. The diffusion is governed by the negative Pucci operator. In the linear case, this system was previously investigated by Caffarelli, Patrizi, and Quitalo in J. Eur. Math. Soc. 19, 3575–3628 (2017) as a model in population dynamics. We establish the existence of solutions and prove convergence as $$\varepsilon \rightarrow 0^+$$ to a free boundary problem in which populations remain segregated at a positive distance. In addition, we show that the supports of the limiting functions are sets of finite perimeter and satisfy a semi-convexity property.

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Journal
La Matematica
Published
2026-03-09
DOI
https://doi.org/10.1007/s44007-026-00198-w
Primary Topic
Mathematical Biology Tumor Growth
Type
article
Field-Weighted Citation Impact
0.00

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article

A Nonlinear Model for Long-Range Segregation

Stefania Patrizi, H. T. Chuah, Mónica Torres
La Matematica
Mathematical Biology Tumor Growth
article

A Nonlinear Model for Long-Range Segregation

Stefania Patrizi, H. T. Chuah, Mónica Torres
article en

Abstract

We study a system of fully nonlinear elliptic equations, depending on a small parameter $$\varepsilon $$ , that models long-range segregation of populations. The diffusion is governed by the negative Pucci operator. In the linear case, this system was previously investigated by Caffarelli, Patrizi, and Quitalo in J. Eur. Math. Soc. 19, 3575–3628 (2017) as a model in population dynamics. We establish the existence of solutions and prove convergence as $$\varepsilon \rightarrow 0^+$$ to a free boundary problem in which populations remain segregated at a positive distance. In addition, we show that the supports of the limiting functions are sets of finite perimeter and satisfy a semi-convexity property.

La MatematicaVol. 5(1)
Purdue University West Lafayette (US), The University of Texas at Austin (US)
National Science Foundation
Reduced inequalities
Openalex Percentile: Top 35%
Mathematical Biology Tumor Growth
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