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Stellar masses of SDSS-III/BOSS galaxies at z ∼ 0.5 and constraints to galaxy formation models

219

Citations

145

References

2013

Year

Abstract

We calculate stellar masses for massive luminous galaxies at redshift 0.2-0.7\nusing the first two years of data from the Baryon Oscillation Spectroscopic\nSurvey (BOSS). Stellar masses are obtained by fitting model spectral energy\ndistributions to u,g,r,i,z magnitudes, and simulations with mock galaxies are\nused to understand how well the templates recover the stellar mass. Accurate\nBOSS spectroscopic redshifts are used to constrain the fits. We find that the\ndistribution of stellar masses in BOSS is narrow (Delta log M~0.5 dex) and\npeaks at about logM ~ 11.3 (for a Kroupa initial stellar mass function), and\nthat the mass sampling is uniform over the redshift range 0.2 to 0.6, in\nagreement with the intended BOSS target selection. The galaxy masses probed by\nBOSS extend over ~10^{12} M, providing unprecedented measurements of the\nhigh-mass end of the galaxy mass function. We find that the galaxy number\ndensity above ~ 2.5 10^{11} M agrees with previous determinations. We perform a\ncomparison with semi-analytic galaxy formation models tailored to the BOSS\ntarget selection and volume, in order to contain incompleteness. The abundance\nof massive galaxies in the models compare fairly well with the BOSS data, but\nthe models lack galaxies at the massive end. Moreover, no evolution with\nredshift is detected from ~0.6 to 0.4 in the data, whereas the abundance of\nmassive galaxies in the models increases to redshift zero. Additionally, BOSS\ndata display colour-magnitude (mass) relations similar to those found in the\nlocal Universe, where the most massive galaxies are the reddest. On the other\nhand, the model colours do not display a dependence on stellar mass, span a\nnarrower range and are typically bluer than the observations. We argue that the\nlack of a colour-mass relation for massive galaxies in the models is mostly due\nto metallicity, which is too low in the models.\n

References

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