We consider the problem of approximate sampling from the finite volume Gibbs measure with a general pair interaction. We exhibit a parallel dynamics (Probabilistic Cellular Automaton) which efficiently implements the sampling. In this dynamics the product measure that gives the new configuration in each site contains a term that tends to favour the original value of each spin. This is the main ingredient that allows one to prove that the stationary distribution of the PCA is close in total variation to the Gibbs measure. The presence of the parameter that drives the "inertial" term mentioned above gives the possibility to control the degree of parallelism of the numerical implementation of the dynamics.

Pra, P., Scoppola, B., Scoppola, E. (2012). Sampling from a Gibbs Measure with Pair Interaction by Means of PCA. JOURNAL OF STATISTICAL PHYSICS, 149(4), 722-737 [10.1007/s10955-012-0612-9].

Sampling from a Gibbs Measure with Pair Interaction by Means of PCA

SCOPPOLA, BENEDETTO;
2012-01-01

Abstract

We consider the problem of approximate sampling from the finite volume Gibbs measure with a general pair interaction. We exhibit a parallel dynamics (Probabilistic Cellular Automaton) which efficiently implements the sampling. In this dynamics the product measure that gives the new configuration in each site contains a term that tends to favour the original value of each spin. This is the main ingredient that allows one to prove that the stationary distribution of the PCA is close in total variation to the Gibbs measure. The presence of the parameter that drives the "inertial" term mentioned above gives the possibility to control the degree of parallelism of the numerical implementation of the dynamics.
2012
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore MAT/07 - FISICA MATEMATICA
English
Con Impact Factor ISI
Probabilistic Cellular Automata; Markov Chain Monte Carlo; Gibbs measure
Pra, P., Scoppola, B., Scoppola, E. (2012). Sampling from a Gibbs Measure with Pair Interaction by Means of PCA. JOURNAL OF STATISTICAL PHYSICS, 149(4), 722-737 [10.1007/s10955-012-0612-9].
Pra, P; Scoppola, B; Scoppola, E
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/90394
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