Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

(Monte Carlo) time after time

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Beichl, I. ; Comput. & Appl. Math. Lab., NIST, Gaithersburg, MD, USA ; Sullivan, F.

N. Metropolis's (1953) algorithm has often been used for simulating physical systems that pass among a set of states, with the probabilities of the system being in such states distributed like the Boltzmann function. There are literally thousands of different applications in the physical sciences and elsewhere. In this article, we explain how to reformulate the basic Metropolis algorithm so as to avoid the do-nothing steps and reduce the running time, while also keeping track of the simulated time as determined by the Metropolis algorithm. By the simulated time, we mean the number of Monte Carlo steps that would have been taken if the basic Metropolis algorithm had been used. This approach has already proved successful when used for parallel simulations of molecular beam epitaxy. We show an example.

Published in:

Computational Science & Engineering, IEEE  (Volume:4 ,  Issue: 3 )