Monte Carlo Simulation Techniques

J. Qiang
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引用次数: 1

Abstract

Monte Carlo simulations are widely used in many areas including particle accelerators. In this lecture, after a short introduction and reviewing of some statistical backgrounds, we will discuss methods such as direct inversion, rejection method, and Markov chain Monte Carlo to sample a probability distribution function, and methods for variance reduction to evaluate numerical integrals using the Monte Carlo simulation. We will also briefly introduce the quasi-Monte Carlo sampling at the end of this lecture.
蒙特卡罗模拟技术
蒙特卡罗模拟广泛应用于包括粒子加速器在内的许多领域。在本讲座中,我们将在简单介绍和回顾一些统计背景后,讨论直接反演、拒绝法、马尔可夫链蒙特卡罗等方法对概率分布函数进行抽样,以及使用蒙特卡罗模拟计算数值积分的方差缩减方法。在本讲座的最后,我们还将简要介绍拟蒙特卡罗采样。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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