Exponential bulges in late-type spirals: an improved description of the light distribution

In many cases the modelling of spiral galaxies by an exponential disc and an r1/4-law bulge does not satisfactorily describe the mean radial distribution of light. This is most evident in non-linear least-squares fitting techniques in which the resulting effective radius and surface brightness of the bulge are characterized by large uncertainties and are scattered over large ranges, in sharp contrast to their disc counterparts. We attempt to decompose the major-axis profiles of 34 late-type spirals in terms of an alternative model consisting of an exponential disc and an exponential bulge, using seeing-convolved models. The results of this decomposition show that this model is superior in the statistical aspects of the fitting procedure, in the sense that the various goodness-of-fit indicators are better and the residuals are smaller. The fact that it also confines the parameters of the bulge to a range whose narrowness is comparable to that of the parameters of the disc indicates that this model has the potential to give a better and more consistent description of the bulges of late-type spirals

Structure and star formation in disc galaxies - I. Sample selection and near-infrared imaging

The definitive version is available at www.blackwell-synergy.com '.Copyright Blackwell Publishing DOI : 10.1046/j.1365-8711.2003.06846.xPeer reviewe

An evolutionary approach to modeling radial brightness distributions in elliptical galaxies

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.