Monte Carlo methods. Vol. 1: basics
Monte Carlo methods. Vol. 1: basics
Random number generators: good ones are hard to find
Communications of the ACM
What Do You Care What Other People Think?: Further Adventures of a Curious Character
What Do You Care What Other People Think?: Further Adventures of a Curious Character
FPGA acceleration of a quantum Monte Carlo application
Parallel Computing
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Monte Carlo methods fulfil an important dual role. At a specific level, they provide a general-purpose numerical approach to problems in a wide range of topics. Using such methods, we can explore the characteristics of specific systems without introducing untestable approximations. To show the generality and breadth of Monte Carlo approaches and to point out characteristics of the methods that offer significant potential for development, we look at several prototypical problems in chemistry. In particular, we apply a variety of Monte Carlo methods to problems in the chemistry of clusters. In chemical parlance, a cluster is a group of atoms, whether bonded into molecules or not, that are close enough to experience interatomic or intermolecular forces. Interesting in their own right, clusters also serve as useful prototypes in the study of interfacial and bulk systems generally. (Interfacial systems contain boundary regions between distinct thermodynamic phases, eg., solid/liquid or gas/solid and bulk systems are homogeneous).