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.
(17926 views)
Book cover: Computational PhysicsComputational Physics
by - ETH Zurich
Contents: Introduction; The Classical Few-Body Problem; Partial Differential Equations;The classical N-body problem; Integration methods; Percolation; Magnetic systems; The quantum one-body problem; The quantum N body problem; and more.
(12170 views)
Book cover: High Performance Computing and Numerical ModellingHigh Performance Computing and Numerical Modelling
by - 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.
(13121 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.
(10342 views)