**Monte Carlo: Basics**

by K. P. N. Murthy

**Publisher**: arXiv 2001**Number of pages**: 76

**Description**:

An introduction to the basics of Monte Carlo is given. The topics covered include, sample space, events, probabilities, random variables, mean, variance, covariance, characteristic function, chebyshev inequality, law of large numbers, central limit theorem (stable distribution, Levy distribution), random numbers (generation and testing), random sampling techniques (inversion, rejection, sampling from a Gaussian, Metropolis sampling), analogue Monte Carlo and Importance sampling (exponential biasing, spanier technique).

Download or read it online for free here:

**Download link**

(560KB, PDF)

## Similar books

**Physical Mathematics**

by

**Michael P. Brenner**-

**Harvard University**

This is an introduction to mathematical methods for solving hard mathematics problems that arise in the sciences -- physical, biological and social. Our aim therefore is to teach how computer simulations and analytical calculations can be combined.

(

**5656**views)

**Introduction To Monte Carlo Algorithms**

by

**Werner Krauth**-

**CNRS-Laboratoire de Physique Statistique**

The author discusses the fundamental principles of thermodynamic and dynamic Monte Carlo methods in a simple light-weight fashion. The keywords are Markov chains, Sampling, Detailed Balance, A Priori Probabilities, Rejections, Ergodicity, etc.

(

**7909**views)

**Multigrid Methods for Structured Grids and their Application in Particle Simulation**

by

**Matthias Bolten**-

**John von Neumann Institute for Computing**

This work is focused on the application of multigrid methods to particle simulation methods. Particle simulation is important for a broad range of scientific fields, like biophysics, astrophysics or plasma physics, to name a few.

(

**4836**views)

**Introduction to Monte Carlo Methods**

by

**Stefan Weinzierl**-

**arXiv**

These lectures given to graduate students in high energy physics, provide an introduction to Monte Carlo methods. After an overview of classical numerical quadrature rules, Monte Carlo integration and variance-reducing techniques is introduced.

(

**6916**views)