Global Martingale Entropy Solutions to the Stochastic Isentropic Euler Equations

TL;DR

This paper proves the existence of global martingale entropy solutions for the stochastic isentropic Euler equations using a novel stochastic compactness framework, overcoming challenges posed by stochastic forcing.

Contribution

It introduces a stochastic compensated compactness framework in $L^p$ to establish global solutions without uniform $L^{ abla}$ bounds, advancing the analysis of stochastic Euler systems.

Findings

Established existence of solutions with finite relative-energy.

Proved solutions satisfy local energy inequalities for all adiabatic exponents.

Developed a new stochastic compactness method applicable to similar problems.

Abstract

We establish the existence and compactness of global martingale entropy solutions with finite relative-energy for the stochastically forced system of isentropic Euler equations governed by a general pressure law. To achieve these, a stochastic compensated compactness framework in $L^p$ is developed to overcome the difficulty that the uniform $L^{\infty}$ bound for the stochastic approximate solutions is unavailable, owing to the stochastic forcing term. The convergence of the vanishing viscosity method is established by employing the stochastic compactness framework, along with careful uniform estimates of the stochastic approximate solutions, to obtain the existence of global martingale entropy solutions with finite relative-energy. In particular, in the polytropic pressure case for all adiabatic exponents, we prove that the global solutions satisfy the local mechanical energy inequality when the initial data are only required to have finite relative-energy (while the higher moment estimates for entropy are not required here, as needed in the earlier work). Higher-order relative energy estimates for approximate solutions are also derived to establish the entropy inequality for more convex entropy pairs and to then prove the compactness of solutions to the stochastic isentropic Euler system. The stochastic compensated compactness framework and the uniform estimate techniques for approximate solutions developed in this paper should be useful in the study of other similar problems.