The Stability of Steady-State Hot-Spot Patterns for a Reaction-Diffusion Model of Urban Crime
Theodore Kolokolnikov, Michael Ward, Juncheng Wei

TL;DR
This paper analyzes the existence and stability of localized hot-spot patterns of criminal activity in a reaction-diffusion model of urban crime, identifying thresholds for pattern stability and types of instabilities.
Contribution
It introduces new stability analysis techniques for hot-spot patterns in the crime model, including nonlocal eigenvalue problems and thresholds for instabilities.
Findings
Hot-spot patterns are stable in certain parameter regimes.
A critical number of hot-spots, K_c, determines pattern stability.
Oscillatory instabilities are rare and explicitly studied for single hot-spots.
Abstract
The existence and stability of localized patterns of criminal activity are studied for the reaction-diffusion model of urban crime that was introduced by Short et. al. [Math. Models. Meth. Appl. Sci., 18, Suppl. (2008), pp. 1249--1267]. Such patterns, characterized by the concentration of criminal activity in localized spatial regions, are referred to as hot-spot patterns and they occur in a parameter regime far from the Turing point associated with the bifurcation of spatially uniform solutions. Singular perturbation techniques are used to construct steady-state hot-spot patterns in one and two-dimensional spatial domains, and new types of nonlocal eigenvalue problems are derived that determine the stability of these hot-spot patterns to time-scale instabilities. From an analysis of these nonlocal eigenvalue problems, a critical threshold is determined such that…
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Taxonomy
TopicsMathematical and Theoretical Epidemiology and Ecology Models · Nonlinear Dynamics and Pattern Formation · Mathematical Biology Tumor Growth
