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 ThermodynamicsComputational Thermodynamics
by
Computational foundation of thermodynamics based on deterministic finite precision computation without resort to statistics. A new 2nd Law without the concept of entropy is proved to be a consequence of the 1st Law and finite precision computation.
(9116 views)
Book cover: Introduction to Computational PhysicsIntroduction to Computational Physics
by - 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.
(7159 views)
Book cover: Introduction to Monte Carlo MethodsIntroduction to Monte Carlo Methods
by - 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.
(6530 views)
Book cover: Computational Physics: Problem Solving with ComputersComputational Physics: Problem Solving with Computers
by - Wiley-VCH
This text surveys many of the topics of modern computational physics from a computational science point of view. Its emphasis on learning by doing (assisted by many model programs), as with 2nd Edition, but with new materials as well as with Python.
(2042 views)