Monte Carlo Methods in Statistical Physics
Universities Press, 2004 - 144 pagine
Monte Carlo simulations comprise a substantial part of the new and third major arm of investigation in the physical sciences that has emerged in recent times, to augment the traditional ones of experiment and theory. With the advent of high-speed digital computing, numerical simulations techniques like Monte Carlo have been very successful in extracting real world observations out of seemingly intractable theoretical models.
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What is a Monte Carlo Method?
Random sampling techniques
Monte Carlo integration
Ising spin model
Monte Carlo averages and error bars
What is the nfold way?
HoshenKopelman cluster counting algorithm
What are the improvements to
Entropic or multicanonical sampling
arXiv average B. A. Berg Boltzmann bond percolation canonical ensemble Central Limit Theorem Chem closed system cluster algorithm cluster counting cluster label Comp congruential consider correlation critical slowing denote detailed balance dimensional distribution ensemble of microstates entropic entropic function entropic sampling eprint equilibrium exponential finite flip fluctuation theorem fluctuations free energy Gaussian given hence histogram Hoshen importance sampling Ising model iteration Jarzynski's equality K. P. N. Murthy Kalpakkam KF-CK cluster large number Lett LL(l macroscopic property magnetic Markov chain Marsaglia Metropolis algorithm microcanonical microstates molecular dynamics Monte Carlo estimate Monte Carlo method Monte Carlo simulation multicanonical Monte Carlo multicanonical sampling n-fold nearest neighbour nonequilibrium number of spins order phase transition percolation Phys probability problem pseudo random number random sampling random variable randomly sample space spin configurations square lattice statistical error statistical mechanics statistical physics stochastic Swendsen-Wang algorithm temperature transition matrix update variance Wang zero