Advances in Computer Simulation
Advances in Computer Simulation Lectures Held at the Eötvös Summer School in Budapest, Hungary, 16–20 July 1996 / [electronic resource] :
edited by János Kertész, Imre Kondor.
- VIII, 168 p. 35 illus. online resource.
- Lecture Notes in Physics, 501 0075-8450 ; .
- Lecture Notes in Physics, 501 .
to Monte Carlo algorithms -- Cluster algorithms -- Optimized monte carlo methods -- Monte Carlo on parallel and vector computers -- Error estimates on averages of correlated data -- Stochastic differential equations -- Frustrated systems: Ground state properties via combinatorial optimization -- Molecular dynamics.
Computer simulation has become a basic tool in many branches of physics such as statistical physics, particle physics, or materials science. The application of efficient algorithms is at least as important as good hardware in large-scale computation. This volume contains didactic lectures on such techniques based on physical insight. The emphasis is on Monte Carlo methods (introduction, cluster algorithms, reweighting and multihistogram techniques, umbrella sampling), efficient data analysis and optimization methods, but aspects of supercomputing, the solution of stochastic differential equations, and molecular dynamics are also discussed. The book addresses graduate students and researchers in theoretical and computational physics.
9783540696759
10.1007/BFb0105456 doi
Computer simulation.
Mathematical physics.
Statistical physics.
Simulation and Modeling.
Mathematical Methods in Physics.
Numerical and Computational Physics, Simulation.
Complex Systems.
Atomic, Molecular, Optical and Plasma Physics.
Statistical Physics and Dynamical Systems.
QA76.9.C65
003.3
to Monte Carlo algorithms -- Cluster algorithms -- Optimized monte carlo methods -- Monte Carlo on parallel and vector computers -- Error estimates on averages of correlated data -- Stochastic differential equations -- Frustrated systems: Ground state properties via combinatorial optimization -- Molecular dynamics.
Computer simulation has become a basic tool in many branches of physics such as statistical physics, particle physics, or materials science. The application of efficient algorithms is at least as important as good hardware in large-scale computation. This volume contains didactic lectures on such techniques based on physical insight. The emphasis is on Monte Carlo methods (introduction, cluster algorithms, reweighting and multihistogram techniques, umbrella sampling), efficient data analysis and optimization methods, but aspects of supercomputing, the solution of stochastic differential equations, and molecular dynamics are also discussed. The book addresses graduate students and researchers in theoretical and computational physics.
9783540696759
10.1007/BFb0105456 doi
Computer simulation.
Mathematical physics.
Statistical physics.
Simulation and Modeling.
Mathematical Methods in Physics.
Numerical and Computational Physics, Simulation.
Complex Systems.
Atomic, Molecular, Optical and Plasma Physics.
Statistical Physics and Dynamical Systems.
QA76.9.C65
003.3