Population-based Monte Carlo algorithms

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  • 16 August 2000
Abstract
We give a cross-disciplinary survey on "population-based" Monte Carlo algorithms. These algorithms consist of a set of "walkers" or "particles" for the representation of a high-dimensional vector and the computation is carried out by a random walk and split/deletion of these objects. The algorithms are developed in various fields in physics and statistical sciences and called by lots of different terms -- "Quantum Monte Carlo", "Transfer Matrix Monte Carlo", "Monte Carlo Filter (Particle Filter)","Sequential Monte Carlo" and "PERM" etc. Here we discuss them in a coherent framework. We also touch on related algorithms -- Genetic Algorithms and Annealed Importance Sampling. ### This survey is originally written for statisticians and computer scientists, but will also be useful to physicists.

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