The SDSS DR6 luminosity functions of galaxies
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Abstract:
We present number counts, luminosity functions (LFs) and luminosity densities of galaxies obtained using the Sloan Digital Sky Survey Sixth Data Release in all SDSS photometric bands. Thanks to the SDSS DR6, galaxy statistics have increased by a factor of ~9 in the u-band and by a factor of ~4-5 in the rest of the SDSS bands with respect to the previous work of Blanton et al. (2003b). In addition, we have achieved a high redshift completeness in our galaxy samples. Firstly, by making use of the survey masks, provided by the NYU-VAGC DR6, we have been able to define an area on the sky of high angular redshift completeness. Secondly, we guarantee that brightness-dependent redshift incompleteness is small within the magnitude ranges that define our galaxy samples. With these advances, we have estimated very accurate SDSS DR6 LFs in both the bright and the faint end. In the {0.1}^r-band, our SDSS DR6 luminosity function is well fitted by a Schechter LF with parameters Phi_{*}=0.90 +/- 0.07$, M_{*}-5log_{10}h=-20.73 +/- 0.04 and alpha=-1.23 +/- 0.02. As compared with previous results, we find some notable differences. In the bright end of the {0.1}^u-band luminosity function we find a remarkable excess, of ~1.7 dex at M_{{0.1}^u}=-20.5, with respect to the best-fit Schechter LF. This excess weakens in the {0.1}^g-band, fading away towards the very red {0.1}^z-band. A preliminary analysis on the nature of this bright-end bump reveals that it is mostly comprised of active galaxies and QSOs. It seems, therefore, that an important fraction of this exceeding luminosity may come from nuclear activity. In the faint end of the SDSS DR6 luminosity functions, where we can reach 1-1.5 magnitudes deeper than the previous SDSS LF estimation, we obtain a steeper slope [ABRIDGED].Keywords:
Stellar mass
We test the correlation found by Reichart et al. between time variability and peak luminosity of gamma-ray bursts (GRBs). Recently, Guidorzi et al. found that this still holds for a sample of 32 GRBs with spectroscopic redshift, although with a larger scatter than that originally found by Reichart et al. However, Guidorzi et al. also found that a power law does not provide a good description of that. We report on the same test performed on a sample of 551 burst and transient source experiment (BATSE) GRBs with a significant measure of variability assuming the pseudo-redshifts derived by Band et al. (1186 GRBs) through the anticorrelation between spectral lag and peak luminosity. We still find a correlation between variability as defined by Reichart et al. and peak luminosity with higher significance. However, this subsample of BATSE GRBs shows a higher scatter around the best-fitting power law than that found by Reichart et al. in the variability/peak luminosity space. This is in agreement with the result found by Guidorzi et al. on a sample of 32 GRBs with measured redshift. These results confirm that a power law does not provide a satisfactory description for all the GRBs, in contrast with the original findings by Reichart et al.
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We show that binned differential luminosity functions constructed using the 1/Va method have a significant systematic error for objects close to the flux limit(s) of their parent sample. This is particularly noticeable when luminosity functions are produced for a number of different redshift ranges as is common in the study of AGN or galaxy evolution. We present a simple method of constructing a binned luminosity function which overcomes this problem and has a number of other advantages over the traditional 1/Va method. We also describe a practical method for comparing binned and model luminosity functions, by calculating the expectation values of the binned luminosity function from the model. Binned luminosity functions produced by the two methods are compared for simulated data and for the Large Bright QSO Survey (LBQS). It is shown that the 1/Va method produces a very misleading picture of evolution in the LBQS. The binned luminosity function of the LBQS is then compared with a model two-power-law luminosity function undergoing pure luminosity evolution from Boyle et al. The comparison is made using a model luminosity function averaged over each redshift shell, and using the expectation values for the binned luminosity function calculated from the model. The luminosity function averaged in each redshift shell gives a misleading impression that the model over predicts the number of QSOs at low luminosity even for 1.0 < z < 1.5, when model and data are consistent. The expectation values show that there are significant differences between model and data: the model overpredicts the number of low luminosity sources at both low and high redshift. The luminosity function does not appear to steepen relative to the model as redshift increases.
Luminosity distance
Mass-to-light ratio
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