BookDOI
Monte Carlo Methods in Statistical Physics
Kurt Binder
- Vol. 7
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The article was published on 1979-01-01. It has received 847 citations till now. The article focuses on the topics: Monte Carlo method in statistical physics & Dynamic Monte Carlo method.read more
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Theory of first-order phase transitions
TL;DR: In this paper, a review of various concepts about first-order phase transitions is given, with particular emphasis on metastable states near first order phase transitions, on the'stability limits' of such states (e.g., the spinodal curve of the gas-liquid transition) and on the dynamic mechanisms by which metastable state decay (nucleation and growth of droplets of a new phase).
Journal ArticleDOI
The upstart algorithm: a method for constructing and training feedforward neural networks
TL;DR: Simulations suggest that this method for building and training multilayer perceptrons composed of linear threshold units is efficient in terms of the numbers of units constructed, and the networks it builds can generalize over patterns not in the training set.
Journal ArticleDOI
The impact of quorum sensing and swarming motility on Pseudomonas aeruginosa biofilm formation is nutritionally conditional
Joshua D. Shrout,David L. Chopp,Collin L. Just,Morten Hentzer,Michael Givskov,Matthew R. Parsek +5 more
TL;DR: Examination of pilA and fliM mutant strains supported the role of swarming motility in biofilm formation, and led to a model proposing that the prevailing nutritional conditions dictate the contributions of quorum sensing and swarming Motility at a key juncture early inBiofilm development.
Journal ArticleDOI
Learning in feedforward layered networks: the tiling algorithm
Marc Mézard,Jean-P Nadal +1 more
TL;DR: A new algorithm which builds a feedforward layered network in order to learn any Boolean function of N Boolean units, which is an algorithm for growth of the network, which adds layers, and units inside a layer, at will until convergence.
Journal ArticleDOI
Theory of genetic algorithms
TL;DR: In this article, the authors investigate spectral and geometric properties of the mutation-crossover operator in a genetic algorithm with general-size alphabet and show how the crossover operator enhances the averaging procedure of the genetic algorithm in the random generator phase.