Dirac Concentrations in a Chemostat Model of Adaptive Evolution

作者：Lorz Alexander^*; Perthame Benoit; Taing Cecile

来源：Chinese Annals of Mathematics Series B, 2017, 38(2): 513-538.

DOI：10.1007/s11401-017-1081-x

• Adaptive evolution
• Asymptotic behaviour
• Chemostat
• Dirac concentrations
• Hamilton-Jacobi equations
• Lotka-Volterra equations
• Viscosity solutions

This paper deals with a non-local parabolic equation of Lotka-Volterra type that describes the evolution of phenotypically structured populations. Nonlinearities appear in these systems to model interactions and competition phenomena leading to selection. In this paper, the equation on the structured population is coupled with a differential equation on the nutrient concentration that changes as the total population varies.
Different methods aimed at showing the convergence of the solutions to a moving Dirac mass are reviewed. Using either weak or strong regularity assumptions, the authors study the concentration of the solution. To this end, BV estimates in time on appropriate quantities are stated, and a constrained Hamilton-Jacobi equation to identify where the solutions concentrates as Dirac masses is derived.

• 出版日期2017-3
• 单位INRIA