Multi-dimensional Burgers equation with unbounded initial data: well-posedness and dispersive estimates

TL;DR

This paper extends the well-posedness of the multi-dimensional Burgers equation to unbounded initial data in various L^p spaces and establishes new dispersive estimates using advanced analytical techniques.

Contribution

It proves the unique extension of the solution semi-group to unbounded initial data in L^p spaces and introduces new dispersive estimates for the multi-dimensional Burgers equation.

Findings

Extension of semi-group to unbounded initial data in L^p spaces

Solutions are entropy solutions in extended L^p spaces

New dispersive estimates based on Compensated Integrability and De Giorgi iteration

Abstract

The Cauchy problem for a scalar conservation laws admits a unique entropy solution when the data $u_0$ is a bounded measurable function (Kruzhkov). The semi-group $(S_t)_{t\ge0}$ is contracting in the $L^1$-distance. For the multi-dimensional Burgers equation, we show that $(S_t)_{t\ge0}$ extends uniquely as a continuous semi-group over $L^p(\mathbb{R}^n)$ whenever $1\le p<\infty$, and $u(t):=S_tu_0$ is actually an entropy solution to the Cauchy problem. When $p\le q\le \infty$ and $t>0$, $S_t$ actually maps $L^p(\mathbb{R}^n)$ into $L^q(\mathbb{R}^n)$. These results are based upon new dispersive estimates. The ingredients are on the one hand Compensated Integrability, and on the other hand a De Giorgi-type iteration.