论文标题
Lagrangian模型的参数汉密尔顿方程用于被动标量梯度
Parametric Hamilton's equations for Lagrangian model for passive scalar gradients
论文作者
论文摘要
在随机系统的Instanton方法的背景下，本文的目的是修改汉密尔顿方程的Arclength参数化，允许任意intermanton速度。本文的主要结果是：（i）它将参数化的汉密尔顿方程推广到所需的任何速度。 （ii）在哈密顿量很小但有限的情况下纠正参数作用，以及如何适应概率密度函数（PDF）。 （iii）通过噪声和传播器的重归于偶数近似对PDF的近似。作为上述设置的应用，我们预测了拉格朗日模型中被动标量梯度的统计数据，即标量梯度最近的流体变形闭合（SGRFD）。
In the context of instanton method for stochastic system this paper purposes a modification of the arclength parametrization of the Hamilton's equations allowing for an arbitrary instanton speed. The main results of the paper are: (i) it generalizes the parametrized Hamilton's equations to any speed required. (ii) corrects the parametric action on the occasion that the Hamiltonian is small but finite and how it adjusts to the probability density function (pdf). (iii) Improves instanton approximation to pdf by noise and propagator renormalization. As an application of the above set up we predict the statistics of passive scalar gradients in a Lagrangian model for turbulence, namely the scalar gradient Recent Fluid Deformation Closure (sgRFD).
