Stochastic cluster algorithms for discrete gaussian (SOS) models

H.G. Evertz, M. Hasenbusch, M. Marcu, K. Pinn, Sorin Solomon

Research output: Contribution to journalArticlepeer-review


We present new Monte Carlo cluster algorithms which eliminate critical slowing down in the simulation of solid-on-solid models. In this letter we focus on the two-dimensional discrete gaussian model. The algorithms are based on reflecting the integer valued spin variables with respect to appropriately chosen reflection planes. The proper choice of the reflection plane turns out to be crucial in order to obtain a small dynamical exponent z. Actually, the successful versions of our algorithm are a mixture of two different procedures for choosing the reflection plane, one of them ergodic but slow, the other one non-ergodic and also slow when combined with a Metropolis algorithm.

Original languageEnglish
Pages (from-to)185-191
JournalPhysics Letters B
Issue number1-2
Publication statusPublished - 1991
Externally publishedYes


Dive into the research topics of 'Stochastic cluster algorithms for discrete gaussian (SOS) models'. Together they form a unique fingerprint.

Cite this