Aims. This paper is the second in a series, implementing a classification system for Gaia observations of unresolved galaxies. Our goals are to determine spectral classes and estimate intrinsic astrophysical parameters via synthetic templates. Here we describe (1) a new extended library of synthetic galaxy spectra; (2) its comparison with various observations; and (3) first results of classification and parametrization experiments using simulated Gaia spectrophotometry of this library. Methods. Using the PÉGASE.2 code, based on galaxy evolution models that take account of metallicity evolution, extinction correction, and emission lines (with stellar spectra based on the BaSeL library), we improved our first library and extended it to cover the domain of most of the SDSS catalogue. Our classification and regression models were support vector machines (SVMs). Results. We produce an extended library of 28 885 synthetic galaxy spectra at zero redshift covering four general Hubble types of galaxies, over the wavelength range between 250 and 1050 nm at a sampling of 1 nm or less. The library is also produced for 4 random values of redshift in the range of 0-0.2. It is computed on a random grid of four key astrophysical parameters (infall timescale and 3 parameters defining the SFR) and, depending on the galaxy type, on two values of the age of the galaxy. The synthetic library was compared and found to be in good agreement with various observations. The first results from the SVM classifiers and parametrizers are promising, indicating that Hubble types can be reliably predicted and several parameters estimated with low bias and variance.

Abstract. The method developed by Gouliermis et al. (2000, Paper I), for the detection and classification of stellar systems in the LMC, was used for the identification of stellar associations and open clusters in the central area of the LMC. This method was applied on the stellar catalog produced from a scanned 1.2 m UK Schmidt Telescope Plate in U with a field of view almost 6.• 5 × 6.• 5, centered on the Bar of this galaxy. The survey of the identified systems is presented here followed by the results of the investigation on their spatial distribution and their structural parameters, as were estimated according to our proposed methodology in Paper I. The detected open clusters and stellar associations show to form large filamentary structures, which are often connected with the loci of HI shells. The derived mean size of the stellar associations in this survey was found to agree with the average size found previously by other authors, for stellar associations in different galaxies. This common size of about 80 pc might represent a universal scale for the star formation process, whereas the parameter correlations of the detected loose systems support the distinction between open clusters and stellar associations.

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Aims. The Gaia astrometric survey mission will, as a consequence of its scanning law, obtain low resolution optical (330-1000 nm) spectrophotometry of several million unresolved galaxies brighter than V = 22. We present the first steps in a project to design and implement a classification system for these data. The goal is both to determine morphological classes and to estimate intrinsic astrophysical parameters via synthetic templates. Here we describe (1) a new library of synthetic galaxy spectra, and (2) first results of classification and parametrization experiments using simulated Gaia spectrophotometry of this library. Methods. We have created a large grid of synthetic galaxy spectra using the PÉGASE.2 code, which is based on galaxy evolution models that take into account metallicity evolution, extinction correction, emission lines (with stellar spectra based on the BaSeL library). Our classification and regression models are Support Vector Machines (SVMs), which are kernel-based nonlinear estimators. Results. We produce a basic library of about 3600 zero redshift galaxy spectra covering the main Hubble types over wavelength range 250 to 1050 nm at a sampling of 1 nm or less. It is computed on a regular grid of four key astrophysical parameters for each type and for intermediate random values of the same parameters. An extended library reproduces this at a series of redshifts. Initial results from the SVM classifiers and parametrizers are promising, indicating that Hubble types can be reliably predicted and several parameters estimated with low bias and variance. Comparing the colours of our synthetic library with Sloan Digital Sky Survey (SDSS) spectra we find good agreement over the full range of Hubble types and parameters.