Distributions of Galaxy Spectral Types in the Sloan Digital Sky Survey

Abstract

We perform an objective classification of 170,000 galaxy spectra in the Sloan Digital Sky Survey (SDSS) using the Karhunen-Loève (KL) transform. With about one-sixth of the total set of galaxy spectra that will be obtained by the survey, we are able to carry out the most extensive analysis of its kind to date. The formalism proposed by Connolly and Szalay is adopted to correct for gappy regions in the spectra and to derive eigenspectra and eigencoefficients. From this analysis, we show that this gap-correction formalism leads to a converging set of eigenspectra and KL-repaired spectra. Furthermore, KL eigenspectra of galaxies are found to be convergent not only as a function of iteration, but also as a function of the number of randomly selected galaxy spectra used in the analysis. From these data a set of 10 eigenspectra of galaxy spectra are constructed, with rest-wavelength coverage 3450-8350 8. The eigencoefficients describing these galaxies naturally place the spectra into several classes defined by the plane formed by the first three eigencoefficients of each spectrum. Spectral types corresponding to different Hubble types and galaxies with extreme emission lines are identified for the 170,000 spectra and are shown to be complementary to existing spectral classifications. From a nonparametric classification technique, we find that the population of galaxies can be divided into three classes that correspond to early late-type through intermediate late-type galaxies. This finding is believed to be related to the color separation of SDSS galaxies discussed in earlier works. Bias in the spectral classifications due to the aperture spectroscopy in the SDSS is small and within the signal-to-noise limit for a majority of galaxies, except for the reddest nearby galaxies and large galaxies (>30 kpc) with prominent emissions. The mean spectra and eigenspectra derived from this work can be downloaded from the SDSS Web site.

Photometric redshifts for the SDSS Data Release 12

“…The modelling of emission lines in such models -which 1 http://skyserver.sdss.org/CasJobs/ 2 http://www.vo.elte.hu/papers/2016/photoz/ can contribute significantly to broad-band magnitudes (Atek et al 2011) -is a difficulty because of the number of extra parameters needed to model the interstellar medium, but additional theoretical assumptions (Stasińska 1984;Fioc & Rocca-Volmerange 1997;Ferland et al 2013) or empirical line estimation (Győry et al 2011;Beck et al 2016) can still be used. Alternatively, sets of measured galaxy spectra can be used to compile a library of empirical spectral templates, where the inclusion of measured lines is relatively straightforward (Yip et al 2004;Dobos et al 2012;Marchetti et al 2013).…”

Active Galactic Nuclei in the Sloan Digital Sky Survey. I. Sample Selection

“…In this paper the library is constructed by applying the principal component analysis ( PCA) technique (e.g., Connolly et al 1995;Lahav et al 1996;Bromley et al 1998;Eisenstein et al 2003;Yip et al 2004) to a sample of pure absorption-line galaxies.…”

First-Year Spectroscopy for the Sloan Digital Sky Survey-Ii Supernova Survey

“…In this procedure, each observed spectrum is modeled by a weighted combination of SN templates (identical to those used for the cross-correlations analysis) and PCA eigenspectra derived from the SDSS galaxy sample (Yip et al 2004). The redshift is fixed to the value determined by the cross-correlation procedure above, but we allow the flux from the SN and the three dominant PCA galaxy components to vary.…”

“…where D is the observed host + SN spectrum, S is the SN template spectrum at an epoch T , G 0 , G 1 , and G 2 are the first three major PCA eigenspectra of the SDSS galaxy sample (Yip et al 2004), A λ is the extinction (applied at the redshift of the SN), and σ is the 1σ error of the spectrum. Here a, b 0 , b 1 , b 2 , and c are constants to be adjusted for the best fit in the SN spectra, host galaxy, and reddening space.…”