Optimized monte carlo methods

  • Enzo Marinari
Conference paper
Part of the Lecture Notes in Physics book series (LNP, volume 501)


I discuss optimized data analysis and Monte Carlo methods. Reweighting methods are discussed through examples, such as Lee-Yang zeroes in the Ising model and the absence of deconfinement in QCD. Reweighted data analysis and multihistogramming are also discussed. I introduce simulated tempering, and, as an example, its application to the random field Ising model. I illustrate parallel tempering, and discuss some crucial technical details such as thermalization and volume scaling. I give a general perspective by discussing umbrella methods and the multicanonical approach.


Partition Function Wilson Loop Ising Model Lattice Gauge Theory Complex Zero 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag 1998

Authors and Affiliations

  • Enzo Marinari
    • 1
  1. 1.Dipartimento di FisicaUniversità di CagliariCagliariItaly

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