Global well-posedness to stochastic reaction-diffusion equations on the real line $\mathbb{R}$ with superlinear drifts driven by multiplicative space-time white noise
Shijie Shang, Tusheng Zhang

TL;DR
This paper proves the existence and uniqueness of global solutions for stochastic reaction-diffusion equations with logarithmic nonlinearity on the entire real line driven by space-time white noise, overcoming previous obstacles related to solution explosion.
Contribution
It introduces a novel approach using a specially designed norm and new moment estimates to establish well-posedness on , extending prior results from compact intervals.
Findings
Established global well-posedness on for equations with superlinear drifts.
Developed new moment estimates for stochastic convolution.
Created a novel Gronwall's inequality applicable to this context.
Abstract
Consider the stochastic reaction-diffusion equation with logarithmic nonlinearity driven by space-time white noise: \begin{align}\label{1.a} \left\{ \begin{aligned} & \mathrm{d}u(t,x) = \frac{1}{2}\Delta u(t,x)\,\mathrm{d}t+ b(u(t,x)) \,\mathrm{d}t \nonumber\\ & ~~~~~~~~~~~~~~~~ + \sigma(u(t,x)) \,W(\mathrm{d}t,\mathrm{d}x), \ t>0, x\in I , \\ & u(0,x)=u_0(x), \quad x\in I .\nonumber \end{aligned} \right. \end{align} When is a compact interval, say , the well-posedness of the above equation was established in [DKZ] (Ann. Prob. 47:1,2019). The case where was left open. The essential obstacle is caused by the explosion of the supremum norm of the solution, , making the usual truncation procedure invalid. In this paper, we prove that there exists a unique global solution to the stochastic reaction-diffusion equation on the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic processes and financial applications · advanced mathematical theories · Mathematical Biology Tumor Growth
