The Speed of a Random Front for Stochastic Reaction–Diffusion Equations with Strong Noise

We study the asymptotic speed of a random front for solutions $u_t(x)$ to stochastic reaction-diffusion equations of the form \[ \partial_tu=\farc{1}{2}\partial_x^2u+f(u)+\sigma\sqrt{u(1-u)}\dot{W}(t,x),~t\ge 0,~x\in\Rm, \] arising in population genetics. Here, $f$ is a continuous function with $f(0)=f(1)=0$, and such that~$|f(u)|\le K|u(1-u)|^\gamma$ with~$\gamma\ge 1/2$, and $\dot{W}(t,x)$ is a space-time Gaussian white noise. We assume that the initial condition $u_0(x)$ satisfies $0\le u_0(x)\le 1$ for all $x\in\Rm$, $u_0(x)=1$ for~$x R_0$. We show that when $\sigma>0$, for each $t>0$ there exist~$R(u_t) R(u_t)$ and $u_t(x)=1$ for~$x 0$ there exists a finite deterministic speed~$V(\sigma)\in\Rm$ so that~$R(u_t)/t\to V(\sigma)$ as $t\to+\infty$, almost surely. This is in dramatic contrast with the deterministic case $\sigma=0$ for nonlinearities of the type $f(u)=u^m(1-u)$ with $0 1/2$ there exists $c_f\in\Rm$, so that~$\sigma^2V(\sigma)\to c_f$ as~$\sigma\to+\infty$ and give a characterization of $c_f$. The last result complements a lower bound obtained by Conlon and Doering \cite{cd05} for the special case of $f(u)=u(1-u)$ where a duality argument is available.