
I 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.
Lectures given at the 1996 Budapest Summer School on Monte Carlo Methods. 35 pages including 17 figures
High Energy Physics - Lattice, Statistical Mechanics (cond-mat.stat-mech), High Energy Physics - Lattice (hep-lat), FOS: Physical sciences, Disordered Systems and Neural Networks (cond-mat.dis-nn), Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Statistical Mechanics
High Energy Physics - Lattice, Statistical Mechanics (cond-mat.stat-mech), High Energy Physics - Lattice (hep-lat), FOS: Physical sciences, Disordered Systems and Neural Networks (cond-mat.dis-nn), Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Statistical Mechanics
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