Lp-regularity theory for semilinear stochastic partial differential equations with multiplicative white noise

preprint2022arXivOpen access

Abstract

We establish the LpL_p-regularity theory for a semilinear stochastic partial differential equation with multiplicative white noise: $$ du = (a^{ij}u_{x^ix^j} + b^{i}u_{x^i} + cu + \bar b^{i}|u|^λu_{x^i})dt + σ^k(u)dw_t^k,\quad (t,x)\in(0,\infty)\times\bR^d; \quad u(0,\cdot) = u_0, $$ where λ>0λ>0, the set {wtk,k=1,2,… }\{ w_t^k,k=1,2,\dots \} is a set of one-dimensional independent Wiener processes, and the function u0=u0(ω,x)u_0 = u_0(ω,x) is a nonnegative random initial data. The coefficients aij,bi,ca^{ij},b^i,c depend on (ω,t,x)(ω,t,x), and bˉi\bar b^i depends on (ω,t,x1,…,xi−1,xi+1,…,xd)(ω,t,x^1,\dots,x^{i-1},x^{i+1},\dots,x^d). The coefficients aij,bi,c,bˉia^{ij},b^i,c,\bar{b}^i are uniformly bounded and twice continuous differentiable. The leading coefficient aa satisfies ellipticity condition. Depending on the diffusion coefficient σk(u)σ^k(u), we consider two different cases; (i) λ∈(0,∞)λ\in(0,\infty) and σk(u)σ^k(u) has Lipschitz continuity and linear growth in uu, (ii) λ,λ0∈(0,1/d)λ,λ_0\in(0,1/d) and σk(u)=μk∣u∣1+λ0σ^k(u) = μ^k |u|^{1+λ_0} (σk(u)σ^k(u) is super-linear). Each case has different regularity results. For example, in the case of (i)(i), for ε>0\varepsilon>0 $$u \in C^{1/2 - \varepsilon,1 - \varepsilon}_{t,x}([0,T]\times\bR^d)\quad \forall T<\infty, $$ almost surely. On the other hand, in the case of (ii)(ii), if λ,λ0∈(0,1/d)λ,λ_0\in(0,1/d), for ε>0\varepsilon>0 $$ u \in C^{\frac{1-(λd) \vee (λ_0 d)}{2} - \varepsilon,1-(λd) \vee (λ_0 d) - \varepsilon}_{t,x}([0,T]\times\bR^d)\quad \forall T<\infty $$ almost surely. It should be noted that λλ can be any positive number and the solution regularity is independent of nonlinear terms in case (i)(i). In case (ii)(ii), however, λ,λ0λ,λ_0 should satisfy λ,λ0∈(0,1/d)λ,λ_0\in(0,1/d) and the regularities of the solution are affected by λ,λ0λ,λ_0 and dd.

Explore this paper’s authors, topics and related work.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Reviews 0

Write a reviewWrite

No reviews yet.

Discussion 0

Add a commentWrite

No comments yet.