论文标题
部分可观测时空混沌系统的无模型预测
On Laplacian eigenvalue equation with constant Neumann boundary data
论文作者
论文摘要
储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。
Let $Ω$ be a bounded Lipshcitz domain in $\mathbb{R}^n$ and we study boundary behaviors of solutions to the Laplacian eigenvalue equation with constant Neumann data. \begin{align} \label{cequation0} \begin{cases} -Δu=cu\quad &\mbox{in $Ω$}\\ \frac{\partial u}{\partial ν}=-1\quad &\mbox{on $\partial Ω$}. \end{cases} \end{align}First, by using properties of Bessel functions and proving new inequalities on elementary symmetric polynomials, we obtain the following inequality for rectangular boxes, balls and equilateral triangles: \begin{align} \label{bbb} \lim_{c\rightarrow μ_2^-}c\int_{\partial Ω}u_c\, dσ\ge \frac{n-1}{n}\frac{P^2(Ω)}{|Ω|}, \end{align}with equality achieved only at cubes and balls. In the above, $u_c$ is the solution to the eigenvalue equation and $μ_2$ is the second Neumann Laplacian eigenvalue. Second, let $κ_1$ be the best constant for the Poincaré inequality with mean zero on $\partial Ω$, and we prove that $κ_1\le μ_2$, with equality holds if and only if $\int_{\partial Ω}u_c\, dσ>0$ for any $c\in (0,μ_2)$. As a consequence, $κ_1=μ_2$ on balls, rectangular boxes and equilateral triangles, and balls maximize $κ_1$ over all Lipschitz domains with fixed volume. As an application, we extend the symmetry breaking results from ball domains obtained in Bucur-Buttazzo-Nitsch[J. Math. Pures Appl., 2017], to wider class of domains, and give quantitative estimates for the precise breaking threshold at balls and rectangular boxes. It is a direct consequence that for domains with $κ_1<μ_2$, the above boundary limit inequality is never true, while whether it is valid for domains on which $κ_1=μ_2$ remains open.