Monte Carlo Simulation Techniques
Computational Physics
2020-06-19 v1 Accelerator Physics
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.
Cite
@article{arxiv.2006.10506,
title = {Monte Carlo Simulation Techniques},
author = {Ji Qiang},
journal= {arXiv preprint arXiv:2006.10506},
year = {2020}
}
Comments
11 pages, contribution to the CAS - CERN Accelerator School: Numerical Methods for Analysis, Design and Modelling of Particle Accelerators, 11-23 November 2018, Thessaloniki, Greece