Practical Guide to Monte Carlo
Computational Physics
2007-05-23 v1 Astrophysics
High Energy Physics - Phenomenology
Data Analysis, Statistics and Probability
Abstract
I show how to construct Monte Carlo algorithms (programs), prove that they are correct and document them. Complicated algorithms are build using a handful of elementary methods. This construction process is transparently illustrated using graphical representation in which complicated graphs consist of only several elementary building blocks. In particular I discuss the equivalent algorithms, that is different MC algorithms, with different arrangements of the elementary building blocks, which generate the same final probability distribution. I also show how to transform a given MC algorithm into another equivalent one and discuss advantages of the various ``architectures''.
Cite
@article{arxiv.physics/9906056,
title = {Practical Guide to Monte Carlo},
author = {S. Jadach},
journal= {arXiv preprint arXiv:physics/9906056},
year = {2007}
}