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arXiv 2009.01006cond-mat.stat-mechphysics.comp-phphysics.flu-dyn
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非线性随机Langevin回归建模

Nonlinear stochastic modeling with Langevin regression

Jared L. Callaham, Jean-Christophe Loiseau, Georgios Rigas, Steven L. Brunton

摘要:

许多物理系统的非线性多尺度相互作用的特点可以有效地模拟处理未解决的自由度作为随机波动。然而,即使当微观控制方程和定性宏观行为是已知的,它往往是很难推导出一个随机模型,是一致的观察。这对于诸如湍流的系统尤其如此,其中扰动的行为不像高斯白噪声,将非马尔可夫行为引入动力学。我们解决这些挑战的框架识别可解释的随机非线性动力学的实验数据,使用前向和伴随福克-普朗克方程,以执行统计一致性。如果朗之万方程的形式是未知的,一个简单的稀疏化过程可以提供一个适当的函数形式。我们证明,这种方法可以有效地学习随机模型在两个人工的例子:恢复非线性朗之万方程强迫色噪声和近似的二阶动力学的粒子在双势阱与相应的一阶分岔规范形式。最后,我们将所提出的方法应用到湍流钝体尾流的实验测量中,并表明压力中心的统计行为可以由非线性状态相关噪声驱动的相应层流的动力学来描述。

英文摘要:

Many physical systems characterized by nonlinear multiscale interactions can be effectively modeled by treating unresolved degrees of freedom as random fluctuations. However, even when the microscopic governing equations and qualitative macroscopic behavior are known, it is often difficult to derive a stochastic model that is consistent with observations. This is especially true for systems such as turbulence where the perturbations do not behave like Gaussian white noise, introducing non-Markovian behavior to the dynamics. We address these challenges with a framework for identifying interpretable stochastic nonlinear dynamics from experimental data, using both forward and adjoint Fokker-Planck equations to enforce statistical consistency. If the form of the Langevin equation is unknown, a simple sparsifying procedure can provide an appropriate functional form. We demonstrate that this method can effectively learn stochastic models in two artificial examples: recovering a nonlinear Langevin equation forced by colored noise and approximating the second-order dynamics of a particle in a double-well potential with the corresponding first-order bifurcation normal form. Finally, we apply the proposed method to experimental measurements of a turbulent bluff body wake and show that the statistical behavior of the center of pressure can be described by the dynamics of the corresponding laminar flow driven by nonlinear state-dependent noise.

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