Abstract
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 advantage 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.
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References
Andredakis, Y.C., Sanders, R.H.: Exponential bulges in late-type spirals: an improved description of the light distribution. Monthly Notices of the Royal Astronomical Society (MNRAS) 267(2), 283–296 (1994)
De Jong, R.S.: Near-IR photometry of 86 galaxies. II. Astronomy & Astrophysics Supplement Series 118, 557–573 (1996)
De Vaucouleurs, G.: Recherches sur les Nebuleuses Extragalactiques. Annales d’Astrophysique 11, 247 (1948)
Fogel, D.B.: System Identification Through Simulated Evolution: A Machine Learning Approach to Modeling. Needham Heights, MA: Ginn (1991)
Fogel, L.J., Owens, A.J., Walsh, M.J.: Artificial Intelligence Through Simulated Evolution. Wiley, New York (1966)
Freeman, K.C.: On the Disks of Spiral and S0 Galaxies. The Astrophysical Journal 160, 811–830 (1970)
Hubble, E.P.: Distribution of luminosity in elliptical nebulae. The Astrophysical Journal 71, 231–276 (1930)
Khosroshahi, H.G., Raychaudhury, S., Ponman, T.J., Miles, T.A., Forbes, D.A.: Scaling relations in early-type galaxies belonging to groups. Monthly Notices of the Royal Astronomical Society 349, 527–534 (2004)
Khosroshahi, H.G., Wadadekar, Y., Kembhavi, A., Mobasher, B.: Correlations among global photometric properties of disk galaxies. The Astrophysical Journal letters 531, 103–106 (2000a)
Khosroshahi, H.G., Wadadekar, Y., Kembhavi, A.: Correlations among global photometric properties of disk galaxies. The Astrophysical Journal 533, 162–171 (2000b)
King, I.R.: The structure of star clusters. I. An empirical density law. Astronomical Journal 67, 471 (1962)
King, I.R.: The structure of star clusters. III. Some simple dynamical models. Astronomical Journal 71, 64
Kormendy, J.: Brightness distributions in compact and normal galaxies. III - Decomposition of observed profiles into spheroid and disk components. The Astrophysical Journal 217, 406–419 (1977)
Koza, J.R.: Genetic Programming: on the programming of computers by means of natural selection. MIT Press, Cambridge (1992)
Koza, J.R.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge (1994)
Koza, J.R.: Genetic Programming: on the programming of computers by means of natural selection. MIT Press, Cambridge (1992)
Koza, J.R.: Genetic Programming II: Automatic Discovery of Reusable Programs (1994)
Schombert, J.M., Bothun, G.D.: The methodology and reliability of determining bulge-to-disk ratios for spiral galaxies. Astronomical Journal (ISSN 0004-6256) 93, 60–73 (1987)
Sersic, J.L.: Atlas de Galaxies Australes Cordoba: Observatorio Astronomica (1968)
Sparke, L.S., Gallagher III, J.S.: Galaxies in the Universe: An introduction. Cambridge University Press, Cambridge (2000)
Van den Bergh, S.: Galaxy Morphology and classification. Cambridge University Press, Cambridge (1998)
Yao, X.: An overview of evolutionary computation. Chinese J. Adv. Software Res. 3(1), 12–29 (1996)
Yao, X., Liu, Y., Lin, G.: Evolutionary Programming Made Faster. IEEE Transaction on Evolutionary Computation 3(2), 82–102 (1999)
Wadadekar, Y., Robbason, B., Kembhavi, A.: Two-dimensional Galaxy Image Decomposition. Astronomical Journal 117(3), 1219–1228 (1999)
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Li, J., Yao, X., Frayn, C., Khosroshahi, H.G., Raychaudhury, S. (2004). An Evolutionary Approach to Modeling Radial Brightness Distributions in Elliptical Galaxies. In: Yao, X., et al. Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. Lecture Notes in Computer Science, vol 3242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30217-9_60
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DOI: https://doi.org/10.1007/978-3-540-30217-9_60
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