Parallel random number generations for Monte Carlo simulation

2011 ◽  
Author(s):  
Ingyu Lee
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Random Number

scholarly journals ANALYSIS OF RANDOM NUMBER GENERATORS USING MONTE CARLO SIMULATION

1994 ◽  
Vol 05 (03) ◽  
pp. 547-560 ◽  
Author(s):  
P.D. CODDINGTON
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Ising Model ◽  
High Precision ◽  
Random Number ◽  
Statistical Tests ◽  
Exact Results ◽  
Random Number Generators ◽  
Monte Carlo Algorithms

Monte Carlo simulation is one of the main applications involving the use of random number generators. It is also one of the best methods of testing the randomness properties of such generators, by comparing results of simulations using different generators with each other, or with analytic results. Here we compare the performance of some popular random number generators by high precision Monte Carlo simulation of the 2-d Ising model, for which exact results are known, using the Metropolis, Swendsen-Wang, and Wolff Monte Carlo algorithms. Many widely used generators that perform well in standard statistical tests are shown to fail these Monte Carlo tests.

scholarly journals Reliability Evaluation of Roy Billinton Test System

2021 ◽  
Vol 9 (4) ◽  
pp. 491-498
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Random Number ◽  
Test System ◽  
Random Number Generators ◽  
Reliability Indices ◽  
Continuous Power ◽  
Simple Systems ◽  
Planning And Operation

Reliability play's a major role at power system planning and operation. Reliability means continuous power supply to end users without outages. So in order to study reliability of any system we consider two methods which are Analytical and Monte-Carlo simulation. Analytical methods are mathematical models which gives numerical calculations for simple systems. Monte Carlo Simulation is a proposed method which is used in case of complex systems. RBTS BUS-2 test system is used as case study with DG’s at different locations and without DG’s to evaluate fundamental reliability indices, customer oriented indices SAIFI, SAIDI, CAIDI .Cost/worth indices such as EENS, ECOST and IEAR are calculated and compared by both Analytical and Monte-Carlo simulation. In Monte-Carlo time sequential technics indices are calculated by using random number generators with UP and DOWN states times of system elements.

scholarly journals Microtubule Disassembling Through Stathmin Bending Bow: A Molecular Dynamic Study

2021 ◽  
Vol 12 (2) ◽  
pp. 1428-1436
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Molecular Modeling ◽  
Molecular Dynamic ◽  
Growth Rates ◽  
Random Number ◽  
Average Length ◽  
Important Data ◽  
Tubulin Dimer ◽  
Random Position

By this work, molecular modeling has been used to interpret the dynamic instabilities of these macromolecules in their structures. By this investigation, multi-dimension structures of microtubules are fixed in both length and width. Via Monte Carlo simulation, the tubulins have been added from the first side of the tubule towards the opposite side by gradually growing a random position. This method is theoretically accomplished via generating a uniform random number between (0, 1) based on the Monte Carlo approach. Our calculations have been done by proper dimension around 5×10-6 meters of length that consists of 2000 tubulin dimers. The structure growth rates are based on soluble tubulin dimer concentration. Hereby all results were run between 6-12 times in our modeling of any conditions. There have been recorded value numbers, average length, free tubulin concentration, and the important data of thermodynamic parameters for each simulation.

scholarly journals PRM50 Random Number Generators in Monte Carlo Simulation

2012 ◽  
Vol 15 (7) ◽  
pp. A469
Author(s):  
P. Mcewan ◽  
V. Foos ◽  
M. Chraibi ◽  
A. Lloyd ◽  
J.L. Palmer ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Random Number ◽  
Random Number Generators
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