44 research outputs found

    Strong invariance and noise-comparison principles for some parabolic stochastic PDEs

    Full text link
    We consider a system of interacting diffusions on the integer lattice. By letting the mesh size go to zero and by using a suitable scaling, we show that the system converges (in a strong sense) to a solution of the stochastic heat equation on the real line. As a consequence, we obtain comparison inequalities for product moments of the stochastic heat equation with different nonlinearities.Comment: 26 page

    On the chaotic character of the stochastic heat equation, before the onset of intermitttency

    Full text link
    We consider a nonlinear stochastic heat equation tu=12xxu+σ(u)xtW\partial_tu=\frac{1}{2}\partial_{xx}u+\sigma(u)\partial_{xt}W, where xtW\partial_{xt}W denotes space-time white noise and σ:RR\sigma:\mathbf {R}\to \mathbf {R} is Lipschitz continuous. We establish that, at every fixed time t>0t>0, the global behavior of the solution depends in a critical manner on the structure of the initial function u0u_0: under suitable conditions on u0u_0 and σ\sigma, supxRut(x)\sup_{x\in \mathbf {R}}u_t(x) is a.s. finite when u0u_0 has compact support, whereas with probability one, lim supxut(x)/(logx)1/6>0\limsup_{|x|\to\infty}u_t(x)/({\log}|x|)^{1/6}>0 when u0u_0 is bounded uniformly away from zero. This sensitivity to the initial data of the stochastic heat equation is a way to state that the solution to the stochastic heat equation is chaotic at fixed times, well before the onset of intermittency.Comment: Published in at http://dx.doi.org/10.1214/11-AOP717 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

    On the chaotic character of the stochastic heat equation, II

    Full text link
    Consider the stochastic heat equation tu=(ϰ2)Δu+σ(u)F˙\partial_t u = (\frac{\varkappa}{2})\Delta u+\sigma(u)\dot{F}, where the solution u:=ut(x)u:=u_t(x) is indexed by (t,x)(0,)×Rd(t,x)\in (0, \infty)\times\R^d, and F˙\dot{F} is a centered Gaussian noise that is white in time and has spatially-correlated coordinates. We analyze the large-x|x| fixed-tt behavior of the solution uu in different regimes, thereby study the effect of noise on the solution in various cases. Among other things, we show that if the spatial correlation function ff of the noise is of Riesz type, that is f(x)xαf(x)\propto \|x\|^{-\alpha}, then the "fluctuation exponents" of the solution are ψ\psi for the spatial variable and 2ψ12\psi-1 for the time variable, where ψ:=2/(4α)\psi:=2/(4-\alpha). Moreover, these exponent relations hold as long as α(0,d2)\alpha\in(0, d\wedge 2); that is precisely when Dalang's theory implies the existence of a solution to our stochastic PDE. These findings bolster earlier physical predictions

    Semi-discrete, semi-linear SPDEs

    Get PDF
    Consider an infinite system of interacting Ito diffusions, started at a nonnegative deterministic bounded initial profile. We study local and global features of the solution under standard regularity assumptions on the nonlinearity σ. We will show that, locally in time, the solution behaves as a collection of independent diffusions. We prove also that the k-th moment Lyapunov exponent is frequently of sharp quadratic order k^2, in contrast to the continuous-space stochastic heat equation whose k-th moment Lyapunov exponent can be of sharp cubic order. When the underlying walk is transient and the noise level is sufficiently low, we prove also that the solution is a.s. uniformly dissipative provided that the initial profile is regular enough
    corecore