Application of Genetic Algorithms to a variety of problems in Physics and Astronomy

Mathematics – Logic

Scientific paper

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Scientific paper

Genetic algorithms are search techniques in which operations are analogous to processes in biological evolution such as natural selection and mutation. They can be employed as robust numerical optimizers on problems that would normally be problematic because of ill-behaved search spaces. Genetic algorithms differ from more conventional, hill-climbing, strategies in that they are global optimization methods that are less likely to terminate at local maxima. We have applied a genetic algorithm to several problems in physics and astronomy, and intend to apply it shortly to parameterization of cross sections for nuclear reaction libraries used extensively in simulations of explosive nucleosynthesis in astrophysical environments such as novae, X-ray bursts, and supernovae. We are also investigating the application of genetic algorithms to the modeling of interacting galaxies. Such modeling could provide a deeper understanding of galaxy formation, as well as "peculiar" galaxies that exhibit such structures as bridges and tidal tails.

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