Stellar Locus Regression: Accurate Color Calibration, and the Real-time Determination of Galaxy Cluster Photometric Redshifts

We present Stellar Locus Regression (SLR), a method of directly adjusting the instrumental broadband optical colors of stars to bring them into accord with a universal stellar color-color locus, producing accurately calibrated colors for both stars and galaxies. This is achieved without first establishing individual zeropoints for each passband, and can be performed in real-time at the telescope. We demonstrate how SLR naturally makes one wholesale correction for differences in instrumental response, for atmospheric transparency, for atmospheric extinction, and for Galactic extinction. We perform an example SLR treatment of SDSS data over a wide range of Galactic dust values and independently recover the direction and magnitude of the canonical Galactic reddening vector with 14--18 mmag RMS uncertainties. We then isolate the effect of atmospheric extinction, showing that SLR accounts for this and returns precise colors over a wide of airmass, with 5--14 mmag RMS residuals. We demonstrate that SLR-corrected colors are sufficiently accurate to allow photometric redshift estimates for galaxy clusters (using red sequence galaxies) with an uncertainty $\sigma(z)/(1+z)$ = 0.6% per cluster for redshifts 0.09< $z$ <0.25. Finally, we identify our objects in the 2MASS all-sky catalog, and produce i-band zeropoints typically accurate to 18 mmag using only SLR. We offer open-source access to our IDL routines, validated and verified for the implementation of this technique, at http://stellar-locus-regression.googlecode.comPhysic

Velocity Segregation and Systematic Biases In Velocity Dispersion Estimates With the SPT-GMOS Spectroscopic Survey

The velocity distribution of galaxies in clusters is not universal; rather, galaxies are segregated according to their spectral type and relative luminosity. We examine the velocity distributions of different populations of galaxies within 89 Sunyaev Zel'dovich (SZ) selected galaxy clusters spanning $0.28 < z < 1.08$. Our sample is primarily draw from the SPT-GMOS spectroscopic survey, supplemented by additional published spectroscopy, resulting in a final spectroscopic sample of 4148 galaxy spectra---2868 cluster members. The velocity dispersion of star-forming cluster galaxies is $17\pm4$% greater than that of passive cluster galaxies, and the velocity dispersion of bright ($m < m^{*}-0.5$) cluster galaxies is $11\pm4$% lower than the velocity dispersion of our total member population. We find good agreement with simulations regarding the shape of the relationship between the measured velocity dispersion and the fraction of passive vs. star-forming galaxies used to measure it, but we find a small offset between this relationship as measured in data and simulations in which suggests that our dispersions are systematically low by as much as 3\% relative to simulations. We argue that this offset could be interpreted as a measurement of the effective velocity bias that describes the ratio of our observed velocity dispersions and the intrinsic velocity dispersion of dark matter particles in a published simulation result. Measuring velocity bias in this way suggests that large spectroscopic surveys can improve dispersion-based mass-observable scaling relations for cosmology even in the face of velocity biases, by quantifying and ultimately calibrating them out.Comment: Accepted to ApJ; 21 pages, 11 figures, 5 table

A First Catalog of Variable Stars Measured by the Asteroid Terrestrial-impact Last Alert System (ATLAS)

The Asteroid Terrestrial-impact Last Alert System (ATLAS) carries out its primary planetary defense mission by surveying about 13000 deg^2 at least four times per night. The resulting data set is useful for the discovery of variable stars to a magnitude limit fainter than r~18, with amplitudes down to 0.01 mag for bright objects. Here we present a Data Release One catalog of variable stars based on analyzing 142 million stars measured at least 100 times in the first two years of ATLAS operations. Using a Lomb-Scargle periodogram and other variability metrics, we identify 4.7 million candidate variables which we analyze in detail. Through Space Telescope Science Institute, we publicly release lightcurves for all of them, together with a vector of 169 classification features for each star. We do this at the level of unconfirmed candidate variables in order to provide the community with a large set of homogeneously analyzed photometry and avoid pre-judging which types of objects others may find most interesting. We use machine learning to classify the candidates into fifteen different broad categories based on lightcurve morphology. About 10% (430,000 stars) pass extensive tests designed to screen out spurious variability detections: we label these as `probable' variables. Of these, 230,000 receive specific classifications as eclipsing binaries, pulsating, Mira-type, or sinusoidal variables: these are the `classified' variables. New discoveries among the probable variables number more than 300,000, while 150,000 of the classified variables are new, including about 10,000 pulsating variables, 2,000 Mira stars, and 70,000 eclipsing binaries.Comment: Accepted by AJ; gives instructions for querying ATLAS variable star database; this new version has nicer lightcurve figure

Constraints on the Progenitor of SN 2016gkg From Its Shock-Cooling Light Curve

SN 2016gkg is a nearby Type IIb supernova discovered shortly after explosion. Like several other Type IIb events with early-time data, SN 2016gkg displays a double-peaked light curve, with the first peak associated with the cooling of a low-mass extended progenitor envelope. We present unprecedented intranight-cadence multi-band photometric coverage of the first light-curve peak of SN 2016gkg obtained from the Las Cumbres Observatory Global Telescope network, the Asteroid Terrestrial-impact Last Alert System, the Swift satellite and various amateur-operated telescopes. Fitting these data to analytical shock-cooling models gives a progenitor radius of ~25-140 solar radii with ~2-30 x 10^-2 solar masses of material in the extended envelope (depending on the model and the assumed host-galaxy extinction). Our radius estimates are broadly consistent with values derived independently (in other works) from HST imaging of the progenitor star. However, the shock-cooling model radii are on the lower end of the values indicated by pre-explosion imaging. Hydrodynamical simulations could refine the progenitor parameters deduced from the shock-cooling emission and test the analytical models.Comment: Accepted by ApJ

A rocky planet transiting a nearby low-mass star

M-dwarf stars -- hydrogen-burning stars that are smaller than 60 per cent of the size of the Sun -- are the most common class of star in our Galaxy and outnumber Sun-like stars by a ratio of 12:1. Recent results have shown that M dwarfs host Earth-sized planets in great numbers: the average number of M-dwarf planets that are between 0.5 to 1.5 times the size of Earth is at least 1.4 per star. The nearest such planets known to transit their star are 39 parsecs away, too distant for detailed follow-up observations to measure the planetary masses or to study their atmospheres. Here we report observations of GJ 1132b, a planet with a size of 1.2 Earth radii that is transiting a small star 12 parsecs away. Our Doppler mass measurement of GJ 1132b yields a density consistent with an Earth-like bulk composition, similar to the compositions of the six known exoplanets with masses less than six times that of the Earth and precisely measured densities. Receiving 19 times more stellar radiation than the Earth, the planet is too hot to be habitable but is cool enough to support a substantial atmosphere, one that has probably been considerably depleted of hydrogen. Because the host star is nearby and only 21 per cent the radius of the Sun, existing and upcoming telescopes will be able to observe the composition and dynamics of the planetary atmosphere.Comment: Published in Nature on 12 November 2015, available at http://dx.doi.org/10.1038/nature15762. This is the authors' version of the manuscrip

Synthesizing Stellar Populations in South Pole Telescope Galaxy Clusters. I. Ages of Quiescent Member Galaxies at 0.3 < z < 1.4

Using stellar population synthesis models to infer star formation histories (SFHs), we analyze photometry and spectroscopy of a large sample of quiescent galaxies that are members of Sunyaev–Zel'dovich (SZ)-selected galaxy clusters across a wide range of redshifts. We calculate stellar masses and mass-weighted ages for 837 quiescent cluster members at 0.3 < z < 1.4 using rest-frame optical spectra and the Python-based Prospector framework, from 61 clusters in the SPT-GMOS Spectroscopic Survey (0.3 < z < 0.9) and three clusters in the SPT Hi-z cluster sample (1.25 < z < 1.4). We analyze spectra of subpopulations divided into bins of redshift, stellar mass, cluster mass, and velocity-radius phase-space location, as well as by creating composite spectra of quiescent member galaxies. We find that quiescent galaxies in our data set sample a diversity of SFHs, with a median formation redshift (corresponding to the lookback time from the redshift of observation to when a galaxy forms 50% of its mass, t50) of z = 2.8 ± 0.5, which is similar to or marginally higher than that of massive quiescent field and cluster galaxy studies. We also report median age–stellar mass relations for the full sample (age of the universe at t50 (Gyr) = 2.52 (±0.04)–1.66 (±0.12) log10(M/1011M⊙)) and recover downsizing trends across stellar mass; we find that massive galaxies in our cluster sample form on aggregate ∼0.75 Gyr earlier than lower-mass galaxies. We also find marginally steeper age–mass relations at high redshifts, and report a bigger difference in formation redshifts across stellar mass for fixed environment, relative to formation redshifts across environment for fixed stellar mass