**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

**High Performance Computing and Numerical Modelling**

by

**Volker Springel**-

**arXiv**

These are lecture notes about high performance computing and numerical modelling in 43rd Saas Fee Advanced Course winter school, specifically covering the basics of numerically treating gravity and hydrodynamics in the context of galaxy evolution.

(

**5115**views)

**Computational Turbulent Incompressible Flow**

by

**Johan Hoffman, Claes Johnson**-

**Springer**

In this book we address mathematical modeling of turbulent fluid flow, and its many mysteries that have haunted scientist over the centuries. We approach these mysteries using a synthesis of computational and analytical mathematics.

(

**8947**views)

**Computational Physics With Python**

by

**Eric Ayars**-

**California State University, Chico**

Contents: Useful Introductory Python; Python Basics; Basic Numerical Tools; Numpy, Scipy, and MatPlotLib; Ordinary Differential Equations; Chaos; Monte Carlo Techniques; Stochastic Methods; Partial Differential Equations; Linux; Visual Python; etc.

(

**4985**views)

**Introduction to Computational Physics**

by

**Franz J. Vesely**-

**University of Vienna**

The essential point in computational physics is the systematic application of numerical techniques in place of, and in addition to, analytical methods, in order to render accessible to computation as large a part of physical reality as possible.

(

**7748**views)