Computer Science
Scientific paper
Oct 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004lncs.3242..591l&link_type=abstract
Lecture Notes in Computer Science, Vol. 3242. Parallel Problem Solving from Nature - PPSN VIII. ISBN 978-3-540-23092-2. Springer
Computer Science
Elliptical Galaxies. Genetic Algorithms
Scientific paper
A reasonably good description of the luminosity profiles of galaxies is needed as it serves as a guide towards understanding the process of galaxy formation and evolution. To obtain a radial brightness profile model of a galaxy, the way varies both in terms of the exact mathematical form of the function used and in terms of the algorithm used for parameters fitting for the function given. Traditionally, one builds such a model by means of fitting parameters for a functional form assumed beforehand. As a result, such a model depends crucially on the assumed functional form. In this paper we propose an approach that enables one to build profile models from data directly without assuming a functional form in advance by using evolutionary computation. This evolutionary approach consists of two major steps that serve two goals. The first step applies the technique of genetic programming with the aim of finding a promising functional form, whereas the second step takes advantag!
e of the power of evolutionary programming with the aim of fitting parameters for functional forms found at the first step. The proposed evolutionary approach has been applied to modeling 18 elliptical galaxies profiles and its preliminary results are reported in this paper.
Frayn Colin
Khosroshahi Habib G.
Li Jin
Raychaudhury Somak
Yao Xin
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