Probabilistic well-posedness of dispersive PDEs beyond variance blowup I: Benjamin-Bona-Mahony equation

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Autori principali: Li, Guopeng, Li, Jiawei, Oh, Tadahiro, Tzvetkov, Nikolay
Natura: Preprint
Pubblicazione: 2025
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author Li, Guopeng
Li, Jiawei
Oh, Tadahiro
Tzvetkov, Nikolay
author_facet Li, Guopeng
Li, Jiawei
Oh, Tadahiro
Tzvetkov, Nikolay
contents We investigate a possible extension of probabilistic well-posedness theory of nonlinear dispersive PDEs with random initial data beyond variance blowup. As a model equation, we study the Benjamin-Bona-Mahony equation (BBM) with Gaussian random initial data. By introducing a suitable vanishing multiplicative renormalization constant on the initial data, we show that solutions to BBM with the renormalized Gaussian random initial data beyond variance blowup converge in law to a solution to the stochastic BBM forced by the derivative of a spatial white noise. By considering alternative renormalization, we show that solutions to the renormalized BBM with the frequency-truncated Gaussian initial data converges in law to a solution to the linear stochastic BBM with the full Gaussian initial data, forced by the derivative of a spatial white noise. This latter result holds for the Gaussian random initial data of arbitrarily low regularity. We also establish analogous results for the stochastic BBM forced by a fractional derivative of a space-time white noise.
format Preprint
id arxiv_https___arxiv_org_abs_2509_02344
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Probabilistic well-posedness of dispersive PDEs beyond variance blowup I: Benjamin-Bona-Mahony equation
Li, Guopeng
Li, Jiawei
Oh, Tadahiro
Tzvetkov, Nikolay
Analysis of PDEs
Probability
35Q35, 35R60, 60H15, 60H30
We investigate a possible extension of probabilistic well-posedness theory of nonlinear dispersive PDEs with random initial data beyond variance blowup. As a model equation, we study the Benjamin-Bona-Mahony equation (BBM) with Gaussian random initial data. By introducing a suitable vanishing multiplicative renormalization constant on the initial data, we show that solutions to BBM with the renormalized Gaussian random initial data beyond variance blowup converge in law to a solution to the stochastic BBM forced by the derivative of a spatial white noise. By considering alternative renormalization, we show that solutions to the renormalized BBM with the frequency-truncated Gaussian initial data converges in law to a solution to the linear stochastic BBM with the full Gaussian initial data, forced by the derivative of a spatial white noise. This latter result holds for the Gaussian random initial data of arbitrarily low regularity. We also establish analogous results for the stochastic BBM forced by a fractional derivative of a space-time white noise.
title Probabilistic well-posedness of dispersive PDEs beyond variance blowup I: Benjamin-Bona-Mahony equation
topic Analysis of PDEs
Probability
35Q35, 35R60, 60H15, 60H30
url https://arxiv.org/abs/2509.02344