论文标题

部分可观测时空混沌系统的无模型预测

Generating Galton-Watson trees using random walks and percolation for the Gaussian free field

论文作者

Drewitz, Alexander, Gallo, Gioele, Prévost, Alexis

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。

The study of Gaussian free field level sets on supercritical Galton-Watson trees has been initiated by Abächerli and Sznitman in Ann. Inst. Henri Poincaré Probab. Stat., 54(1):173--201, 2018. By means of entirely different tools, we continue this investigation and generalize their main result on the positivity of the associated percolation critical parameter $h_*$ to the setting of arbitrary supercritical offspring distribution and random conductances. A fortiori, this provides a positive answer to the open question raised at the end of the aforementioned article. What is more, in our setting it also establishes a rigorous proof of the physics literature mantra that positive correlations facilitate percolation when compared to the independent case. Our proof proceeds by constructing the Galton-Watson tree through an exploration via finite random walk trajectories. This exploration of the tree progressively unveils an infinite connected component in the random interlacements set on the tree, which is stable under small quenched noise. Using a Dynkin-type isomorphism theorem, we then infer the strict positivity of the critical parameter $ h_* .$ As a byproduct of our proof we obtain the transience of the random interlacement set and the level sets of the Gaussian free field above small positive levels on such Galton-Watson trees.

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