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Journal ArticleDOI

Nonuniversal critical dynamics in Monte Carlo simulations

Robert H. Swendsen, +1 more
- 12 Jan 1987 - 
- Vol. 58, Iss: 2, pp 86-88
TLDR
A new approach to Monte Carlo simulations is presented, giving a highly efficient method of simulation for large systems near criticality, despite the fact that the algorithm violates dynamic universality at second-order phase transitions.
Abstract
A new approach to Monte Carlo simulations is presented, giving a highly efficient method of simulation for large systems near criticality. The algorithm violates dynamic universality at second-order phase transitions, producing unusually small values of the dynamical critical exponent.

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Citations
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Journal ArticleDOI

Fast approximate energy minimization via graph cuts

TL;DR: This work presents two algorithms based on graph cuts that efficiently find a local minimum with respect to two types of large moves, namely expansion moves and swap moves that allow important cases of discontinuity preserving energies.
Journal ArticleDOI

Power laws, Pareto distributions and Zipf's law

Mark Newman
- 01 Sep 2005 - 
TL;DR: Some of the empirical evidence for the existence of power-law forms and the theories proposed to explain them are reviewed.
Book

Computer Vision: Algorithms and Applications

TL;DR: Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images and takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene.
Journal ArticleDOI

Markov Chains for Exploring Posterior Distributions

Luke Tierney
- 01 Dec 1994 - 
TL;DR: Several Markov chain methods are available for sampling from a posterior distribution as discussed by the authors, including Gibbs sampler and Metropolis algorithm, and several strategies for constructing hybrid algorithms, which can be used to guide the construction of more efficient algorithms.
Journal ArticleDOI

Non-Uniform Random Variate Generation.

B. J. T. Morgan, +1 more
- 01 Sep 1988 - 
TL;DR: This chapter reviews the main methods for generating random variables, vectors and processes in non-uniform random variate generation, and provides information on the expected time complexity of various algorithms before addressing modern topics such as indirectly specified distributions, random processes, and Markov chain methods.
References
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Journal ArticleDOI

Theory of Dynamic Critical Phenomena

TL;DR: The renormalization group theory has been applied to a variety of dynamic critical phenomena, such as the phase separation of a symmetric binary fluid as mentioned in this paper, and it has been shown that it can explain available experimental data at the critical point of pure fluids, and binary mixtures, and at many magnetic phase transitions.
Journal ArticleDOI

On the random-cluster model: I. Introduction and relation to other models

TL;DR: It is shown that the function which for the random-cluster model plays the role of a partition function, is a generalization of the dichromatic polynomial earlier introduced by Tutte, and related polynomials.
Journal ArticleDOI

Percolation and cluster distribution. I. Cluster multiple labeling technique and critical concentration algorithm

TL;DR: In this article, a new approach for the determination of the critical percolation concentration, percolations probabilities, and cluster size distributions is presented for the Site Percolation problem.
Journal ArticleDOI

The theory of condensation and the critical point

TL;DR: In this paper, the condensation point is marked by a singularity of the thermodynamic potential as conjectured by Mayer, and the singularity turns out to be an essential singularity at which all derivatives remain finite.
Journal ArticleDOI

Clusters and Ising critical droplets: a renormalisation group approach

TL;DR: In this article, the authors employed the Migdal-Kadanoff renormalisation group for two-dimensions to obtain the global phase diagram for the site-bond correlated percolation problem.
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