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Histogram Methods for Monte Carlo Data Analysis

  • R. H. Swendsen
  • A. M. Ferrenberg
Part of the Springer Proceedings in Physics book series (SPPHY, volume 45)

Abstract

In this talk, I will discuss new methods for optimizing the analysis of data from Monte Carlo computer simulations. The heights and locations of peaks in the specific heat and the susceptibility can be found with high accuracy for relatively short simulations. For multiple simulations to cover a wide range of values, explicit error estimates allow objective planning of the lengths of runs and the parameter values to be simulated. Since information can cover a large temperature range, it is possible to include both zero and infinite temperature to generate the free energy and entropy over the full range. The methods are applicable to simulations in a variety of fields related to statistical mechanics.

Keywords

Critical Temperature Monte Carlo Monte Carlo Simulation Ising Model Large Temperature Range 
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 Berlin Heidelberg 1990

Authors and Affiliations

  • R. H. Swendsen
    • 1
  • A. M. Ferrenberg
    • 2
  1. 1.Department of PhysicsCarnegie-Mellon UniversityPittsburghUSA
  2. 2.Center for Simulational Physics, Department of Physics and AstronomyUniversity of GeorgiaAthensUSA

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