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Register a new userThe Stripe 82 Massive Galaxy Project I: Catalog Construction
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Kevin Bundy
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The Stripe 82 Massive Galaxy Catalog (S82-MGC) is the largest-volume stellar mass-limited sample of galaxies beyond z~1 constructed to date. Spanning 139.4 deg2, the S82-MGC includes a mass-limited sample of 41,770 galaxies with log Mstar > 11.2 to z~0.7, sampling a volume of 0.3 Gpc3, roughly equivalent to the volume of the Sloan Digital Sky Survey-I/II (SDSS-I/II) z < 0.15 MAIN sample. The catalog is built on three pillars of survey data: the SDSS Stripe 82 Coadd photometry which reaches r-band magnitudes of 23.5 AB, YJHK photometry at depths of 20th magnitude (AB) from the UK Infrared Deep Sky Survey (UKIDSS) Large Area Survey, and over 70,000 spectroscopic galaxy redshifts from SDSS-I/II and the Baryon Oscillation Spectroscopic Survey (BOSS). We describe the catalog construction and verification, the production of 9-band matched aperture photometry, tests of existing and newly estimated photometric redshifts required to supplement spectroscopic redshifts for 55% of the log Mstar > 11.2 sample, and geometric masking. We provide near-IR based stellar mass estimates and compare these to previous estimates. All catalog products are made publicly available. The S82-MGC not only addresses previous statistical limitations in high-mass galaxy evolution studies but begins tackling inherent data challenges in the coming era of wide-field imaging surveys.
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The average stellar mass (Mstar) of high-mass galaxies (Mstar > 3e11 Msun) is expected to grow by ~30% since z~1, largely through ongoing mergers that are also invoked to explain the observed increase in galaxy sizes. Direct evidence for the corresponding growth in stellar mass has been elusive, however, in part because the volumes sampled by previous redshift surveys have been too small to yield reliable statistics. In this work, we make use of the Stripe 82 Massive Galaxy Catalog to build a mass-limited sample of 41,770 galaxies (Mstar > 1.6e11) with optical to near-IR photometry and a large fraction (>55%) of spectroscopic redshifts. Our sample spans 139 square degrees, significantly larger than most previous efforts. After accounting for a number of potential systematic errors, including the effects of Mstar scatter, we measure galaxy stellar mass functions over 0.3 < z < 0.65 and detect no growth in the typical Mstar of massive galaxies with an uncertainty of 9%. This confidence level is dominated by uncertainties in the star formation history assumed for Mstar estimates, although our inability to characterize low surface-brightness outskirts may be the most important limitation of our study. Even among these high-mass galaxies, we find evidence for differential evolution when splitting the sample by recent star formation (SF) activity. While low-SF systems appear to become completely passive, we find a mostly sub-dominant population of galaxies with residual, but low rates of star formation (~1 Msun/yr) number density does not evolve. Interestingly, these galaxies become more prominent at higher Mstar, representing ~10% of all galaxies at Mstar ~ 1e12 Msun and perhaps dominating at even larger masses.
The Baryon Oscillation Spectroscopic Survey (BOSS) has collected spectra for over one million galaxies at $0.15<z<0.7$ over a volume of 15.3 Gpc$^3$ (9,376 deg$^2$) -- providing us an opportunity to study the most massive galaxy populations with vanishing sample variance. However, BOSS samples are selected via complex color cuts that are optimized for cosmology studies, not galaxy science. In this paper, we supplement BOSS samples with photometric redshifts from the Stripe 82 Massive Galaxy Catalog and measure the total galaxy stellar mass function (SMF) at $zsim0.3$ and $zsim0.55$. With the total SMF in hand, we characterize the stellar mass completeness of BOSS samples. The high-redshift CMASS (constant mass) sample is significantly impacted by mass incompleteness and is 80% complete at $log_{10}(M_*/M_{odot}) >11.6$ only in the narrow redshift range $z=[0.51,0.61]$. The low redshift LOWZ sample is 80% complete at $log_{10}(M_*/M_{odot}) >11.6$ for $z=[0.15,0.43]$. To construct mass complete samples at lower masses, spectroscopic samples need to be significantly supplemented by photometric redshifts. This work will enable future studies to better utilize the BOSS samples for galaxy-formation science.
We present the first set of maps and band-merged catalog from the Herschel Stripe 82 Survey (HerS). Observations at 250, 350, and 500 micron were taken with the Spectral and Photometric Imaging Receiver (SPIRE) instrument aboard the Herschel Space Observatory. HerS covers 79 deg$^2$ along the SDSS Stripe 82 to a depth of 13.0, 12.9, and 14.8 mJy beam$^{-1}$ (including confusion) at 250, 350, and 500 micron, respectively. HerS was designed to measure correlations with external tracers of the dark matter density field --- either point-like (i.e., galaxies selected from radio to X-ray) or extended (i.e., clusters and gravitational lensing) --- in order to measure the bias and redshift distribution of intensities of infrared-emitting dusty star-forming galaxies and AGN. By locating HeRS in Stripe 82, we maximize the overlap with available and upcoming cosmological surveys. The band-merged catalog contains 3.3x10$^4$ sources detected at a significance of >3 $sigma$ (including confusion noise). The maps and catalog are available at http://www.astro.caltech.edu/hers/
We report the first results of a study of variable point sources identified using multi-color time-series photometry from Sloan Digital Sky Survey (SDSS) Stripe 82 over a span of nearly 10 years (1998-2007). We construct a light-curve catalog of 221,842 point sources in the R.A. 0-4 h half of Stripe 82, limited to r = 22.0, that have at least 10 detections in the ugriz bands and color errors of < 0.2 mag. These objects are then classified by color and by cross-matching them to existing SDSS catalogs of interesting objects. We use inhomogeneous ensemble differential photometry techniques to greatly improve our sensitivity to variability. Robust variable identification methods are used to extract 6520 variable candidates in this dataset, resulting in an overall variable fraction of ~2.9% at the level of 0.05 mag variability. A search for periodic variables results in the identification of 30 eclipsing/ellipsoidal binary candidates, 55 RR Lyrae, and 16 Delta Scuti variables. We also identify 2704 variable quasars matched to the SDSS Quasar catalog (Schneider et al. 2007), as well as an additional 2403 quasar candidates identified by their non-stellar colors and variability properties. Finally, a sample of 11,328 point sources that appear to be nonvariable at the limits of our sensitivity is also discussed. (Abridged.)
We present 226 large ultra-diffuse galaxy (UDG) candidates ($r_e > 5.3$arcsec, $mu_{0,g} > 24$ mag arcsec$^{-2}$) in the SDSS Stripe 82 region recovered using our improved procedure developed in anticipation of processing the entire Legacy Surveys footprint. The advancements include less constrained structural parameter fitting, expanded wavelet filtering criteria, consideration of Galactic dust, estimates of parameter uncertainties and completeness based on simulated sources, and refinements of our automated candidate classification. We have a sensitivity $sim$1 mag fainter in $mu_{0,g}$ than the largest published catalog of this region. Using our completeness-corrected sample, we find that (1) there is no significant decline in the number of UDG candidates as a function of $mu_{0,g}$ to the limit of our survey ($sim$ 26.5 mag arcsec$^{-2}$); (2) bluer candidates have smaller Sersic $n$; (3) most blue ($g-r < 0.45$ mag) candidates have $mu_{0,g} lesssim 25$ mag arcsec$^{-2}$ and will fade to populate the UDG red sequence we observe to $sim 26.5$ mag arcsec$^{-2}$; (4) any red UDGs that exist significantly below our $mu_{0,g}$ sensitivity limit are not descended from blue UDGs in our sample; and (5) candidates with lower $mu_{0,g}$ tend to smaller $n$. We anticipate that the final SMUDGes sample will contain $sim$ 30$times$ as many candidates.
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