MONTE CARLO METHODS IN SCIENTIFIC COMPUTINGกก
Time Schedule: June 3, Thurs., 8:30 - 11:00, 14:30 - 17:00
June 4, Fri., 8:30 - 11:00
June 5, Sat., 8:30 - 11:00, 14:30 - 17:00
June 7, Mon., 8:30 - 11:00, 14:30 - 17:00
June 8, Tue., 8:30 - 11:00กก
This mini-course aims to
give an introduction to the
Monte Carlo method. The Monte Carlo method was initially
developed during the 1940s when the electronic computer
was just first available. The Monte Carlo method solves
problems that are intractable by analytic or other means.
The use of Monte Carlo methods spans many areas, such as
phase transitions in condensed matter physics, modeling
of biological molecules, fluid flow, neutron diffusion
in reactor, statistical Bayesian analysis, optimization,
image processing, bioinformatics, etc.
In these lectures, We begin with the basic principles
of Monte Carlo method, introducing in an elementary way
the generation of random numbers, concept of Markov chain,
Metropolis algorithm, and analysis of Monte Carlo data.
We demonstrate the use of Monte Carlo method from applications
in statistical physics, statistics, and other fields.
In the later part of the lectures, we'll present more
advanced topics such as efficient simulation methods
(simulated tempering, multicanonical methods, cluster algorithms).
Graduate students and junior researchers are most suited
for this mini-course. Computers are available for exercises.
Registration: send e-mail to firstname.lastname@example.org