2 title = "Comparison of Point Sets and Sequences for Quasi-Monte Carlo and for Random Number Generation",
4 author = "Pierre L'ecuyer",
8 crossref = "DBLP:conf/seta/2008",
9 bibsource = "DBLP, http://dblp.uni-trier.de",
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30 keywords5 = "Neutron scattering",
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36 @Electronic{ citeulike:867581,
37 abstract = "{Monte Carlo simulations are one of the major tools in statistical physics, complex system science, and other fields, and an increasing number of these simulations is run on distributed systems like clusters or grids. This raises the issue of generating random numbers in a parallel, distributed environment. In this contribution we demonstrate that multiple linear recurrences in finite fields are an ideal method to produce high quality pseudo-random numbers in sequential and parallel algorithms. Their known weakness (failure of sampling points in high dimensions) can be overcome by an appropriate delinearization that preserves all desirable properties of the underlying linear sequence.}",
38 archivePrefix = "arXiv",
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45 keywords = "distributed, monte-carlo, random, simulation",
47 posted-at = "2006-09-26 18:51:08",
49 title = "{Random Numbers for Large Scale Distributed Monte Carlo Simulation}",
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55 abstract = "{The Wolff algorithm is now accepted as the best cluster-flipping Monte Carlo algorithm for beating ''critical slowing down.'' We show how this method can yield incorrect answers due to subtle correlations in ''high quality'' random number generators.}",
56 author = "A. M. Ferrenberg and D. P. Landau and Y. J. Wong",
57 doi = "10.1103/PhysRevLett.69.3382",
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62 title = "{Monte Carlo simulations: Hidden errors from ``good'' random number generators}",
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361 author = "Jacques Bahi and Christophe Guyeux",
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587 title = "A Pseudo Random Numbers Generator Based on Chaotic Iterations. Application to Watermarking",
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