Logo

Monte Carlo: Basics by K. P. N. Murthy

Small book cover: Monte Carlo: Basics

Monte Carlo: Basics
by

Publisher: arXiv
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).

Home page url

Download or read it online for free here:
Download link
(560KB, PDF)

Similar books

Book cover: Computational PhysicsComputational Physics
by - University of Oslo
These notes should train you in an algorithmic approach to problems in the sciences, represented here by the unity of three disciplines, physics, mathematics and informatics. This trinity outlines the emerging field of computational physics.
(10847 views)
Book cover: Scientific ComputingScientific Computing
by - Harvey Mudd College
This course consists of both numerical methods and computational physics. MATLAB is used to solve various computational math problems. The course is primarily for Math majors and supposes no previous knowledge of numerical analysis or methods.
(3213 views)
Book cover: Introduction to Computational Physics and Monte Carlo Simulations of Matrix Field TheoryIntroduction to Computational Physics and Monte Carlo Simulations of Matrix Field Theory
by - arXiv
We give an elementary introduction to computational physics. We deal with the problem of how to set up working Monte Carlo simulations of matrix field theories which involve finite dimensional matrix regularizations of noncommutative field theories.
(3527 views)
Book cover: Introduction To Monte Carlo AlgorithmsIntroduction To Monte Carlo Algorithms
by - 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.
(8649 views)