On a large deviation principle for 1d cubic NLS with optimal decaying data
Fuente:
arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1866915666271928320 |
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| author | Fan, Chenjie Ye, Feng |
| author_facet | Fan, Chenjie Ye, Feng |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_09599 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On a large deviation principle for 1d cubic NLS with optimal decaying data Fan, Chenjie Ye, Feng Analysis of PDEs Probability 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. |
| title | On a large deviation principle for 1d cubic NLS with optimal decaying data |
| topic | Analysis of PDEs Probability |
| url | https://arxiv.org/abs/2512.09599 |