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Monte Carlo simulation on microcomputers
SIMULATION, 1992Monte Carlo analysis is a practical tech nique for including the effects of uncertainty in a model intended for decision support. It has been infrequently used, however, perhaps because it has been tedious and boring to do. A recently available software add-in to 1-2-3 named @Risk makes Monte Carlo analysis much easier.
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Monte Carlo simulation for IRRMA
Applied Radiation and Isotopes, 2000Monte Carlo simulation is fast becoming a standard approach for many radiation applications that were previously treated almost entirely by experimental techniques. This is certainly true for Industrial Radiation and Radioisotope Measurement Applications--IRRMA.
R P, Gardner, L, Liu
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Green Simulation with Database Monte Carlo
ACM Transactions on Modeling and Computer Simulation, 2016In a setting in which experiments are performed repeatedly with the same simulation model, green simulation means reusing outputs from previous experiments to answer the question currently being asked of the model. In this article, we address the setting in which experiments are run to answer questions quickly, with a time limit providing a fixed ...
Mingbin Feng, Jeremy Staum
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Overrelaxation and Monte Carlo simulation
Physical Review D, 1987I study a simple variation of the algorithm of Metropolis et al. for simulating statistical systems. The trial changes in any given variable are taken from a region of phase space far from the old value but involving only small changes in energy. This results in correlation times which are short compared to the usual applications of the algorithm of ...
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2019
The sequential use of random numbers, to sample the values of probability variables, allows obtaining solutions to mathematical problems such as the Monte Carlo method, that allows to model stochastic parameters or deterministic based on random sampling.
Lorenzo Cevallos-Torres +1 more
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The sequential use of random numbers, to sample the values of probability variables, allows obtaining solutions to mathematical problems such as the Monte Carlo method, that allows to model stochastic parameters or deterministic based on random sampling.
Lorenzo Cevallos-Torres +1 more
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Multicanonical Monte Carlo Simulations
International Journal of Modern Physics C, 1993The multicanonical ensemble is reviewed. Simulations of this ensemble promise improvements for a wide range of systems. Applications to first order phase transitions and spin glasses are summarized.
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2014
The name “Monte Carlo” emerged from the name of the city “Monte Carlo”, famous for its Casino. In the casino there was a roulette where a small button was fixed at the centre of a wheel and the numbers 0–9 were marked at the end of the ten spokes of the wheel. When the button was pressed, the wheel starts rotating. When the wheel stops, a number within
Asis Kumar Chattopadhyay +1 more
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The name “Monte Carlo” emerged from the name of the city “Monte Carlo”, famous for its Casino. In the casino there was a roulette where a small button was fixed at the centre of a wheel and the numbers 0–9 were marked at the end of the ten spokes of the wheel. When the button was pressed, the wheel starts rotating. When the wheel stops, a number within
Asis Kumar Chattopadhyay +1 more
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Monte Carlo simulation in Fourier space
Computer Physics Communications, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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2006
In the general overview on materials and their characteristics, outlined in Sect. 1.3, it has been stated that materials and their characteristics result from the processing of matter. Thus, condensed matter physics is one of the fundamentals for the understanding of materials.
Xiao Hu +2 more
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In the general overview on materials and their characteristics, outlined in Sect. 1.3, it has been stated that materials and their characteristics result from the processing of matter. Thus, condensed matter physics is one of the fundamentals for the understanding of materials.
Xiao Hu +2 more
openaire +1 more source

