Luminous Red Galaxies: Selection and classification by combining optical and infrared photometry

We describe a new method of combining optical and infrared photometry to select Luminous Red Galaxies (LRGs) at redshifts $z > 0.6$. We explore this technique using a combination of optical photometry from CFHTLS and HST, infrared photometry from the WISE satellite, and spectroscopic or photometric redshifts from the DEEP2 Galaxy Redshift Survey or COSMOS. We present a variety of methods for testing the success of our selection, and present methods for optimization given a set of rest-frame color and redshift requirements. We have tested this selection in two different regions of the sky, the COSMOS and Extended Groth Strip (EGS) fields, to reduce the effect of cosmic/sample variance. We have used these methods to assemble large samples of LRGs for two different ancillary programs as a part of the SDSS-III/ BOSS spectroscopic survey. This technique is now being used to select $\sim$600,000 LRG targets for SDSS-IV/eBOSS, which began observations in Fall 2014, and will be adapted for the proposed DESI survey. We have found these methods can select high-redshift LRGs efficiently with minimal stellar contamination; this is extremely difficult to achieve with selections that rely on optical photometry alone.Comment: 10 pages, 13 figures, Published in the Astrophysical Journa

Extremely large scale simulation of a Kardar-Parisi-Zhang model using graphics cards

The octahedron model introduced recently has been implemented onto graphics cards, which permits extremely large scale simulations via binary lattice gases and bit coded algorithms. We confirm scaling behaviour belonging to the 2d Kardar-Parisi-Zhang universality class and find a surface growth exponent: beta=0.2415(15) on 2^17 x 2^17 systems, ruling out beta=1/4 suggested by field theory. The maximum speed-up with respect to a single CPU is 240. The steady state has been analysed by finite size scaling and a growth exponent alpha=0.393(4) is found. Correction to scaling exponents are computed and the power-spectrum density of the steady state is determined. We calculate the universal scaling functions, cumulants and show that the limit distribution can be obtained by the sizes considered. We provide numerical fitting for the small and large tail behaviour of the steady state scaling function of the interface width.Comment: 7 pages, 8 figures, slightly modified, accepted version for PR

A Cosmic Variance Cookbook

Deep pencil beam surveys (<1 deg^2) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties are in practice limited by 'cosmic variance'. This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper we provide tools for experiment design and interpretation. For a given survey geometry we present the cosmic variance of dark matter as a function of mean redshift z and redshift bin size Dz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, z, Dz and stellar mass m*. We also provide tabulated values and a software tool. We find that for GOODS at z=2 and with Dz=0.5 the relative cosmic variance of galaxies with m*>10^11 Msun is ~38%, while it is ~27% for GEMS and ~12% for COSMOS. For galaxies of m*~10^10 Msun the relative cosmic variance is ~19% for GOODS, ~13% for GEMS and ~6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at z=2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies cosmic variance is less serious.Comment: 8 pages, 4 figures, 5 tables, submitted to Ap

What Genetics Offers Geobiology

For over 50 years, the Parker Brothers’ board game “Clue” has maintained its position as the classic family detective game. A murder has been committed in the mansion, but we don’t know where, by whom, or how. Was it Professor Plum in the study with a knife, or Miss Scarlett in the ballroom with a candlestick? Through rolls of the dice, fragments of information patiently accumulated piece-by-piece, and the application of logic, players construct a case to figure out “whodunit”. Because there are several potential solutions to the problem, the key challenge is to figure out what happened by understanding how it happened

Measuring galaxy [OII] emission line doublet with future ground-based wide-field spectroscopic surveys

The next generation of wide-field spectroscopic redshift surveys will map the large-scale galaxy distribution in the redshift range 0.7< z<2 to measure baryonic acoustic oscillations (BAO). The primary optical signature used in this redshift range comes from the [OII] emission line doublet, which provides a unique redshift identification that can minimize confusion with other single emission lines. To derive the required spectrograph resolution for these redshift surveys, we simulate observations of the [OII] (3727,3729) doublet for various instrument resolutions, and line velocities. We foresee two strategies about the choice of the resolution for future spectrographs for BAO surveys. For bright [OII] emitter surveys ([OII] flux ~30.10^{-17} erg /cm2/s like SDSS-IV/eBOSS), a resolution of R~3300 allows the separation of 90 percent of the doublets. The impact of the sky lines on the completeness in redshift is less than 6 percent. For faint [OII] emitter surveys ([OII] flux ~10.10^{-17} erg /cm2/s like DESi), the detection improves continuously with resolution, so we recommend the highest possible resolution, the limit being given by the number of pixels (4k by 4k) on the detector and the number of spectroscopic channels (2 or 3).Comment: 5 pages, 1 figur

Measuring Galaxy Environments with Deep Redshift Surveys

We study the applicability of several galaxy environment measures (n^th-nearest-neighbor distance, counts in an aperture, and Voronoi volume) within deep redshift surveys. Mock galaxy catalogs are employed to mimic representative photometric and spectroscopic surveys at high redshift (z ~ 1). We investigate the effects of survey edges, redshift precision, redshift-space distortions, and target selection upon each environment measure. We find that even optimistic photometric redshift errors (\sigma_z = 0.02) smear out the line-of-sight galaxy distribution irretrievably on small scales; this significantly limits the application of photometric redshift surveys to environment studies. Edges and holes in a survey field dramatically affect the estimation of environment, with the impact of edge effects depending upon the adopted environment measure. These edge effects considerably limit the usefulness of smaller survey fields (e.g. the GOODS fields) for studies of galaxy environment. In even the poorest groups and clusters, redshift-space distortions limit the effectiveness of each environment statistic; measuring density in projection (e.g. using counts in a cylindrical aperture or a projected n^th-nearest-neighbor distance measure) significantly improves the accuracy of measures in such over-dense environments. For the DEEP2 Galaxy Redshift Survey, we conclude that among the environment estimators tested the projected n^th-nearest-neighbor distance measure provides the most accurate estimate of local galaxy density over a continuous and broad range of scales.Comment: 17 pages including 16 figures, accepted to Ap