Pointwise convergence problem of Ostrovsky equation with rough data and random data

TL;DR

This paper investigates the pointwise convergence of the Ostrovsky equation for rough and random initial data, establishing convergence results at a certain regularity level and demonstrating failure below that threshold.

Contribution

It proves almost everywhere convergence for data in $H^{s}$ with $s \\geq 1/4$, and almost sure convergence for random data in $L^{2}$, addressing the singularity at zero.

Findings

Almost everywhere convergence for $s \\geq 1/4$ with rough data.

Counterexamples showing failure of maximal estimates when $s<1/4$.

Almost sure convergence for random data in $L^{2}$.

Abstract

In this paper, we consider the pointwise convergence problem of free Ostrovsky equation with rough data and random data. Firstly, we show the almost everywhere pointwise convergence of free Ostrovsky equation in $H^{s}(\mathbb{R})$ with $s\geq \frac{1}{4}$ with rough data. Secondly, we present counterexamples showing that the maximal function estimate related to the free Ostrovsky equation can fail if $s<\frac{1}{4}$. Finally, for every $x\in \mathbb{R}$, we show the almost surely pointwise convergence of free Ostrovsky equation in $L^{2}(\mathbb{R})$ with random data. The main tools are the density theorem, high-low frequency idea, Wiener decomposition and Lemmas 2.1-2.6 as well as the probabilistic estimates of some random series which are just Lemmas 3.2-3.4 in this paper. The main difficulty is that zero is the singular point of the phase functions of free Ostrovsky equation. We use high-low frequency idea to conquer the difficulties.