A regularity theory for stochastic generalized Burgers' equation driven by a multiplicative space-time white noise
Abstract
We introduce the uniqueness, existence, -regularity, and maximal H\"older regularity of the solution to semilinear stochastic partial differential equation driven by a multiplicative space-time white noise: where . The function is either bounded Lipschitz or super-linear in . The noise is a space-time white noise. The coefficients depend on , and depends on . The coefficients are uniformly bounded, and satisfies ellipticity condition. The random initial data is nonnegative. We have the maximal H\"older regularity by employing the H\"older embedding theorem. For example, if and has Lipschitz continuity, linear growth, and boundedness in , for and , On the other hand, if and with , for and , It should be noted that if is bounded Lipschitz in , the H\"older regularity of the solution is independent of . However, if is super-linear in , the H\"older regularities of the solution are affected by nonlinearities, and
Keywords
Cite
@article{arxiv.2111.03659,
title = {A regularity theory for stochastic generalized Burgers' equation driven by a multiplicative space-time white noise},
author = {Beom-Seok Han},
journal= {arXiv preprint arXiv:2111.03659},
year = {2022}
}
Comments
33 pages. arXiv admin note: text overlap with arXiv:2111.03302