论文标题
部分可观测时空混沌系统的无模型预测
Cloudy with A Chance of Rain: Accretion Braking of Cold Clouds
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。
Understanding the survival, growth and dynamics of cold gas is fundamental to galaxy formation. While there has been a plethora of work on `wind tunnel' simulations that study such cold gas in winds, the infall of this gas under gravity is at least equally important, and fundamentally different since cold gas can never entrain. Instead, velocity shear increases and remains unrelenting. If these clouds are growing, they can experience a drag force due to the accretion of low momentum gas, which dominates over ram pressure drag. This leads to sub-virial terminal velocities, in line with observations. We develop simple analytic theory and predictions based on turbulent radiative mixing layers. We test these scalings in 3D hydrodynamic simulations, both for an artificial constant background, as well as a more realistic stratified background. We find that the survival criterion for infalling gas is more stringent than in a wind, requiring that clouds grow faster than they are destroyed ($t_{\rm grow} < 4\,t_{\rm cc} $). This can be translated to a critical pressure, which for Milky Way like conditions is $P \sim 3000 {\rm k}_B {\rm K}\,{\rm cm}^{-3}$ . Cold gas which forms via linear thermal instability ($t_{\rm cool}/t_{\rm ff} < 1$) in planar geometry meets the survival threshold. In stratified environments, larger clouds need only survive infall until cooling becomes effective. We discuss applications to high velocity clouds and filaments in galaxy clusters.