A quasi-Monte Carlo method for the coagulation equation

C. Lécot, A. Tarhini
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引用次数: 1

Abstract

We propose a quasi-Monte Carlo algorithm for the simulation of the continuous coagulation equation. The mass distribution is approximated by a finite number $N$ of numerical particles. Time is discretized and quasi-random points are used at every time step to determine whether each particle is undergoing a coagulation. Convergence of the scheme is proved when $N$ goes to infinity, if the particles are relabeled according to their increasing mass at each time step. Numerical tests show that the computed solutions are in good agreement with analytical ones, when available. Moreover, the error of the QMC algorithm is smaller than the error given by a standard Monte Carlo scheme using the same time step and number $N$ of numerical particles.
混凝方程的拟蒙特卡罗方法
我们提出了一种准蒙特卡罗算法来模拟连续混凝方程。质量分布近似于有限数目的N个数值粒子。将时间离散化,并在每个时间步使用准随机点来确定每个粒子是否正在经历凝聚。当N$趋于无穷时,如果粒子在每个时间步上根据其增加的质量重新标记,则证明了该方案的收敛性。数值试验表明,在可行的情况下,计算解与解析解吻合较好。此外,QMC算法的误差小于使用相同时间步长和数目为N的数值粒子的标准蒙特卡罗格式给出的误差。
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