Multilinear smoothing and local well-posedness of a stochastic quadratic nonlinear Schr{\"o}dinger equation

TL;DR

This paper proves local well-posedness for a stochastic quadratic nonlinear Schrödinger equation driven by irregular noise in dimensions 1 to 3, using multilinear smoothing and Strichartz estimates.

Contribution

It introduces the first local well-posedness results for Schrödinger equations on b^d with irregular noise, combining stochastic multilinear smoothing with deterministic techniques.

Findings

Established local well-posedness for b^d SNLS with fractional noise.

Developed multilinear smoothing estimates for stochastic second-order terms.

Improved well-posedness results for certain noise regularities.

Abstract

In this article, we study a $d$-dimensional stochastic quadratic nonlinear Schr\"{o}dinger equation (SNLS), driven by a fractional derivative (of order $-\alpha<0$) of a space-time white noise: $$\left\{ \begin{array}{l}i\partial_t u-\Delta u= \rho^2 |u|^2 + \langle \nabla \rangle^{-\alpha}\dot{W} \, , \quad t\in [0,T] \, , \, x\in \mathbb{R}^d \, ,\\ u_0 = \phi\, ,\end{array}\right.$$ where $\rho :\mathbb{R}^d \rightarrow \mathbb{R}$ is a smooth compactly-supported function. When $\alpha < \frac{d}{2}$, the stochastic convolution is a function of time with values in a negative-order Sobolev space and the model has to be interpreted in the Wick sense by means of a time-dependent renormalization. When $1\leq d \leq 3$, combining both the classical Strichartz estimates and a deterministic local smoothing, we establish the local well-posedness of (SNLS) for a small range of $\alpha$, in the spirit of \cite{Schaeffer1}. Then, we revisit our arguments and establish multilinear smoothing on the second order stochastic term. This allows us to improve our local well-posedness result for some $\alpha$. We point out that this is the first result concerning a Schr\"{o}dinger equation on $\mathbb{R}^d$ driven by such an irregular noise and whose local well-posedness results from both a stochastic multilinear smoothing and a deterministic local one combined with Strichartz inequalities.