This work is a needed reference for widely used techniques and methods of computer simulation in physics and other disciplines, such as materials science. Molecular dynamics computes a molecule's reactions and dynamics based on physical models; Monte Carlo uses random numbers to…
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Scientists and engineers use computer simulations to study relationships between a model's input parameters and its outputs. However, thorough parameter studies are challenging, if not impossible, when the simulation is expensive and the model has several inputs. To enable studi…
This book gives an introduction to R to build up graphing, simulating and computing skills to enable one to see theoretical and statistical models in economics in a unified way. The great advantage of R is that it is free, extremely flexible and extensible. The book addresses th…
Computer simulation has become an important means for obtaining knowledge about nature. The practice of scientific simulation and the frequent use of uncertain simulation results in public policy raise a wide range of philosophical questions. Most prominently highlighted is the …
Addressing how to manage the science-policy interface, this book presents a philosophical study of the issues surrounding uncertainty in scientific simulation, particularly concerning the role it plays in public policy regarding climate change.
Large-Scale Simulation: Models, Algorithms, and Applications gives you firsthand insight on the latest advances in large-scale simulation techniques. Most of the research results are drawn from the authors, papers in top-tier, peer-reviewed, scientific conference proceedings and…
"Organized to facilitate intuitive learning, this step-by-step manual includes basic and advanced models and algorithms, and software architecture for the implementation of large-scale distributed simulation. An indispensible reference, it offers background information on perfor…