On a large deviation principle for 1d cubic NLS with optimal decaying data
Analysis of PDEs
2025-12-11 v1 Probability
Abstract
In this article, we revisit the work of \cite{garrido2023large}, and prove large deviation principles for more general random initial data for cubic NLS. The Fourier coefficient of our random data admits an optimal polynomial decay.
Keywords
Cite
@article{arxiv.2512.09599,
title = {On a large deviation principle for 1d cubic NLS with optimal decaying data},
author = {Chenjie Fan and Feng Ye},
journal= {arXiv preprint arXiv:2512.09599},
year = {2025}
}
Comments
19 pages, all comments are welcome