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Monte Carlo methods play an important role in scientific computation, especially when problems have a vast phase space.
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Frustrated Spin Systems
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Parallel Tempering: Theory, Applications, and New Perspectives
D. J. Earl and M. W. Deem · 2005
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Rejuvenation and memory in model spin glasses in 3 and 4 dimensions
S. Jimenez, V. Martin-Mayor, and S. Perez-Gaviro · 2005
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On the Efficiency of Exchange in Parallel Tempering Monte Carlo Simulations
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Optimal allocation of replicas in parallel tempering simulations
N. Rathore, M. Chopra, and J. J. de Pablo · 2005
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Free-Energy Barriers in the Sherrington-Kirkpatrick Model
E. Bittner and W. Janke · 2006
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Random Fields and Spin Glasses
C. de Dominicis and I. Giardina · 2006
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Universality in three-dimensional Ising spin glasses: A Monte Carlo study
H. G. Katzgraber, M. Körner, and A. P. Young · 2006
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Feedback-optimized parallel tempering Monte Carlo
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Probing tails of energy distributions using importance-sampling in the disorder with a guiding function
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Algorithms and Computations
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The Parisi formula
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C. M. Newman and D. L. Stein · 2007
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Computer Simulation Studies in Condensed Matter Physics XIX
S. Trebst, D. A. Huse, E. Gull, H. G Katzgraber, U. H. E. Hansmann, and M. Troyer · 2007
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Make life simple: Unleash the full power of the parallel tempering algorithm
E. Bittner, A. Nußbaumer, and W. Janke · 2008
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Ultrametricity and Clustering of States in Spin Glasses: A One-Dimensional View
H. G. Katzgraber and A. K. Hartmann · 2009
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Robust parameter selection for parallel tempering
F. Hamze, N. Dickson, and K. Karimi · 2010
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