Optimized Monte Carlo Methods

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dc.creatorMarinari, Enzo
dc.date1996-11-30
dc.date.accessioned2026-07-07T09:11:20Z
dc.date.available2026-07-07T09:11:20Z
dc.descriptionI discuss optimized data analysis and Monte Carlo methods. Reweighting methods are discussed through examples, like Lee-Yang zeroes in the Ising model and the absence of deconfinement in QCD. I discuss reweighted data analysis and multi-hystogramming. I introduce Simulated Tempering, and as an example its application to the Random Field Ising Model. I illustrate Parallel Tempering, and discuss some technical crucial details like thermalization and volume scaling. I give a general perspective by discussing Umbrella Methods and the Multicanonical approach.
dc.descriptionLectures given at the 1996 Budapest Summer School on Monte Carlo Methods. 35 pages including 17 figures
dc.identifierhttps://arxiv.org/abs/cond-mat/9612010
dc.identifierhttp://arxiv.org/abs/cond-mat/9612010
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/151642
dc.subjectDisordered Systems and Neural Networks
dc.subjectStatistical Mechanics
dc.subjectHigh Energy Physics - Lattice
dc.titleOptimized Monte Carlo Methods
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