[GD98] 7-25 , the SIMBAD biblio

Using the ESO-Sculptor galaxy redshift survey data (ESS), we have extensively tested the Principal Components Analysis (PCA) method to perform the spectral classification of galaxies with z≲0.5. This method allows us to classify all galaxies in an ordered and continuous spectral sequence, which is strongly correlated with the morphological type. The PCA allows to quantify the systematic physical properties of the galaxies in the sample, like the different stellar contributions to the observed light as well as the stellar formation history. We also examine the influence of the emission lines, and the signal-to-noise ratio of the data. This analysis shows that the emission lines play a significant role in the spectral classification, by tracing the activity and abnormal spectral features of the observed sample. The PCA also provides a powerful tool to filter the noise which is carried by the ESS spectra. By comparison of the ESS PCA spectral sequence with that for a selected sample of Kennicutt galaxies (Kennicutt 1992ApJS...79..255K, 1992ApJ...388..310K), we find that the ESS sample contains 26% of E/S0, 71% of Sabc and 3% of Sm/Irr. The type fractions for the ESS show no significant changes in the redshift interval z ∼0.1-0.5, and are comparable to those found in other galaxy surveys at intermediate redshift. The PCA can be used independently from any set of synthetic templates, providing a completely objective and unsupervised method to classify spectra. We compare the classification of the ESS sample given by the PCA, with a χ² test between the ESS sample and galaxy templates from Kennicutt (Kennicutt, 1992ApJS...79..255K), and obtain results in good agreement. The PCA results are also in agreement with the visual morphological classification carried out for the 35 brightest galaxies in the survey.