Convergence to equilibrium for positive solutions of some mutation-selection model

preprint2013arXivOpen access

Abstract

In this paper we are interested in the long time behaviour of the positive solutions of the mutation selection model with Neumann Boundary condition: ∂u(x,t)dt=u[r(x)−∫ØK(x,y)∣u∣p(y) dy]+∇⋅(A(x)∇u(x)),inR+ר \frac{\partial u(x,t)}{dt}=u\left[r(x)-\int_ØK(x,y)|u|^{p}(y)\,dy\right]+\nabla\cdot\left(A(x)\nabla u(x)\right),\qquad \text{in}\quad \R^+\timesØ where Ø⊂RNØ\subset \R^N is a bounded smooth domain, k(.,.)∈C(Øˉ×C(Øˉ),R),p≥1k(.,.) \in C(\bar Ø\times C(\barØ), \R), p\ge 1 and A(x)A(x) is a smooth elliptic matrix. In a blind competition situation, i.e K(x,y)=k(y)K(x,y)=k(y), we show the existence of a unique positive steady state which is positively globally stable. That is, the positive steady state attracts all the possible trajectories initiated from any non negative initial datum. When KK is a general positive kernel, we also present a necessary and sufficient condition for the existence of a positive steady states. We prove also some stability result on the dynamic of the equation when the competition kernel KK is of the form $K(x,y)=k_0(y)+\eps k_1(x,y)$. That is, we prove that for sufficiently small $\eps$ there exists a unique steady state, which in addition is positively asymptotically stable. The proofs of the global stability of the steady state essentially rely on non-linear relative entropy identities and an orthogonal decomposition. These identities combined with the decomposition provide us some a priori estimates and differential inequalities essential to characterise the asymptotic behaviour of the solutions.

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