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Highly accurate tau-leaping methods with random corrections

机译:具有随机校正功能的高精度tau-leaping方法

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We aim to construct higher order tau-leaping methods for numerically simulating stochasticchemical kinetic systems in this paper. By adding a random correction to the primitive tau-leapingscheme in each time step, we greatly improve the accuracy of the tau-leaping approximations. Thisgain in accuracy actually comes from the reduction in the local truncation error of the scheme in theorder of T, the marching time step size. While the local truncation error of the primitive tau-leapingmethod is O(τ~2) for all moments, our Poisson random correction tau-leaping method, in which thecorrection term is a Poisson random variable, can reduce the local truncation error for the mean toO(τ~3), and both Gaussian random correction tau-leaping methods, in which the correction term is aGaussian random variable, can reduce the local truncation error for both the mean and covarianceto O(τ~3).Numerical results demonstrate that these novel methods more accurately capture crucialproperties such as the mean and variance than existing methods for simulating chemical reactionsystems. This work constitutes a first step to construct high order numerical methods for simulatingjump processes. With further refinement and appropriately modified step-size selection procedures,the random correction methods should provide a viable way of simulating chemical reaction systemsaccurately and efficiently.
机译:本文旨在构建用于数值模拟随机化学动力学系统的高阶tau浸出方法。通过在每个时间步中向原始tau-leaping方案添加随机校正,我们极大地提高了tau-leaping近似的准确性。准确性的提高实际上来自于方案的局部截断误差按T(行进时间步长)的顺序减小。当原始tau-leaping方法的局部截断误差在所有时刻均为O(τ〜2)时,我们的Poisson随机校正tau-leaping方法(校正项为Poisson随机变量)可以减少均值的局部截断误差toO(τ〜3)和两种高斯随机校正tau-leaping方法(其中校正项是aGaussian随机变量)均可以减小O(τ〜3)的均值和协方差的局部截断误差。数值结果表明:与现有的模拟化学反应系统的方法相比,这些新颖的方法可以更准确地捕获关键属性,例如均值和方差。这项工作构成了构建用于模拟跳跃过程的高阶数值方法的第一步。通过进一步完善和适当修改步长选择程序,随机校正方法应提供一种准确而有效地模拟化学反应系统的可行方法。

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