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- W2967472783 abstract "We study the two-dimensional stochastic nonlinear wave equation (SNLW) and stochastic nonlinear heat equation (SNLH) with a quadratic nonlinearity, forced by a fractional derivative (of order $alpha > 0$) of a space-time white noise. In particular, we show that the well-posedness theory breaks at $alpha = frac 12$ for SNLW and at $alpha = 1$ for SNLH. This provides a first example showing that SNLW behaves less favorably than SNLH. (i) As for SNLW, Deya (2020) essentially proved its local well-posedness for $0 < alpha < frac 12$. We first revisit this argument and establish multilinear smoothing of order $frac 14$ on the second order stochastic term in the spirit of a recent work by Gubinelli, Koch, and Oh (2018). This allows us to simplify the local well-posedness argument for some range of $alpha$. On the other hand, when $alpha geq frac 12$, we show that SNLW is ill-posed in the sense that the second order stochastic term is not a continuous function of time with values in spatial distributions. This shows that a standard method such as the Da Prato-Debussche trick or its variant, based on a higher order expansion, breaks down for $alpha ge frac 12$. (ii) As for SNLH, we establish analogous results with a threshold given by $alpha = 1$. These examples show that in the case of rough noises, the existing well-posedness theory for singular stochastic PDEs breaks down before reaching the critical values ($alpha = frac 34$ in the wave case and $alpha = 2$ in the heat case) predicted by the scaling analysis (due to Deng, Nahmod, and Yue (2019) in the wave case and due to Hairer (2014) in the heat case)." @default.
- W2967472783 created "2019-08-22" @default.
- W2967472783 creator A5069067766 @default.
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- W2967472783 date "2019-08-09" @default.
- W2967472783 modified "2023-09-23" @default.
- W2967472783 title "Comparing the stochastic nonlinear wave and heat equations: a case study" @default.
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- W2967472783 doi "https://doi.org/10.48550/arxiv.1908.03490" @default.
- W2967472783 hasPublicationYear "2019" @default.
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