Results 261 to 270 of about 512,942 (311)
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Journal of the American Statistical Association, 1949
Abstract In this paper Metropolis and Ulam gave a brief introduction to “the Monte Carlo method” which is described as a statistical approach to the study of differential equations as applied by Metropolis, Ulam, Fermi, von Neumann, Feynman, and others at the Los Alamos Laboratory in the 1940s.0 Several examples of applications of ...
N, METROPOLIS, S, ULAM
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Abstract In this paper Metropolis and Ulam gave a brief introduction to “the Monte Carlo method” which is described as a statistical approach to the study of differential equations as applied by Metropolis, Ulam, Fermi, von Neumann, Feynman, and others at the Los Alamos Laboratory in the 1940s.0 Several examples of applications of ...
N, METROPOLIS, S, ULAM
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Medical Physics, 1979
The generation of long, high quality random number sequences for Monte Carlo simulations using minicomputers is considered. The importance of the thorough testing of Monte Carlo random number generators is emphasized. A recommendation is given to authors of Monte Carlo papers to specify their random number generator and to describe the randomness ...
R L, Morin +3 more
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The generation of long, high quality random number sequences for Monte Carlo simulations using minicomputers is considered. The importance of the thorough testing of Monte Carlo random number generators is emphasized. A recommendation is given to authors of Monte Carlo papers to specify their random number generator and to describe the randomness ...
R L, Morin +3 more
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SIAM Review, 2006
The probability of winning a game, set, match, or single elimination tournament in tennis is computed using Monte Carlo simulations based on each player’s probability of winning a point on serve, which can be held constant or varied from point to point, game to game, or match to match. The theory, described in Newton and Keller [Stud. Appl. Math., 114 (
Paul K. Newton, Kamran Aslam
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The probability of winning a game, set, match, or single elimination tournament in tennis is computed using Monte Carlo simulations based on each player’s probability of winning a point on serve, which can be held constant or varied from point to point, game to game, or match to match. The theory, described in Newton and Keller [Stud. Appl. Math., 114 (
Paul K. Newton, Kamran Aslam
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On Monte Carlo and Quasi-Monte Carlo for Matrix Computations
2018This paper focuses on minimizing further the communications in Monte Carlo methods for Linear Algebra and thus improving the overall performance. The focus is on producing set of small number of covering Markov chains which are much longer that the usually produced ones.
Vassil Alexandrov 0001 +5 more
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Monte Carlo and Quasi-Monte Carlo Methods
2020Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N~1^2), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction ...
Tuffin, Bruno, L'Écuyer, Pierre
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Monte Carlo, Quasi-Monte Carlo, and Randomized Quasi-Monte Carlo
2000This paper surveys recent research on using Monte Carlo techniques to improve quasi-Monte Carlo techniques. Randomized quasi-Monte Carlo methods provide a basis for error estimation. They have, in the special case of scrambled nets, also been observed to improve accuracy.
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Monte Carlo and Quasi-Monte Carlo Methods
2013Chapter 12 discusses Monte Carlo and quasi-Monte Carlo methods and demonstrates how these techniques can be used to compute functionals of multidimensional diffusions. Monte Carlo methods feature prominently in this book, in particular we discuss how to use Lie Symmetry methods to construct unbiased Monte Carlo estimators in Chap. 6, and we discuss how
Jan Baldeaux, Eckhard Platen
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Computing, 1995
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Monte Carlo and quasi-Monte Carlo methods
Acta Numerica, 1998Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N−1/2), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction ...
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Science, 1986
An outline of a random walk computational method for solving the Schrödinger equation for many interacting particles is given, together with a survey of results achieved so far and of applications that remain to be explored. Monte Carlo simulations can be used to calculate accurately the bulk properties of the light elements hydrogen, helium, and ...
D, Ceperley, B, Alder
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An outline of a random walk computational method for solving the Schrödinger equation for many interacting particles is given, together with a survey of results achieved so far and of applications that remain to be explored. Monte Carlo simulations can be used to calculate accurately the bulk properties of the light elements hydrogen, helium, and ...
D, Ceperley, B, Alder
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