Abstract
In this chapter we give a condensed introduction to the basic features of computer simulation methods. We particularly review the Monte Carlo method of importance sampling and the principles of molecular dynamics simulations. Some of the systematic effects associated with computer simulations, such as finite-size effects, statistical errors and so on, are reviewed. The Ising model is introduced in order to provide a concrete illustration of the Monte Carlo method, which will be useful also in later chapters as a simple context in which to present some of the algorithms we will discuss. It is assumed that the reader has at least some prior understanding or experience of the material covered in this chapter, since it is meant mainly as a reference base for the material addressed in subsequent chapters. For a more complete description of the material presented here we recommend referring to one of the number of books that are now available [2.1–5]. The reader embarking upon computer simulations for the first time is encouraged to consult one of these.
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Heermann, D.W., Burkitt, A.N. (1991). Computer Simulation Methods. In: Heermann, D.W., Burkitt, A.N. (eds) Parallel Algorithms in Computational Science. Springer Series in Information Sciences, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76265-9_2
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