The Dark Energy Survey Data Management System

The Dark Energy Survey collaboration will study cosmic acceleration with a 5000 deg2 griZY survey in the southern sky over 525 nights from 2011-2016. The DES data management (DESDM) system will be used to process and archive these data and the resulting science ready data products. The DESDM system consists of an integrated archive, a processing framework, an ensemble of astronomy codes and a data access framework. We are developing the DESDM system for operation in the high performance computing (HPC) environments at NCSA and Fermilab. Operating the DESDM system in an HPC environment offers both speed and flexibility. We will employ it for our regular nightly processing needs, and for more compute-intensive tasks such as large scale image coaddition campaigns, extraction of weak lensing shear from the full survey dataset, and massive seasonal reprocessing of the DES data. Data products will be available to the Collaboration and later to the public through a virtual-observatory compatible web portal. Our approach leverages investments in publicly available HPC systems, greatly reducing hardware and maintenance costs to the project, which must deploy and maintain only the storage, database platforms and orchestration and web portal nodes that are specific to DESDM. In Fall 2007, we tested the current DESDM system on both simulated and real survey data. We used Teragrid to process 10 simulated DES nights (3TB of raw data), ingesting and calibrating approximately 250 million objects into the DES Archive database. We also used DESDM to process and calibrate over 50 nights of survey data acquired with the Mosaic2 camera. Comparison to truth tables in the case of the simulated data and internal crosschecks in the case of the real data indicate that astrometric and photometric data quality is excellent.Comment: To be published in the proceedings of the SPIE conference on Astronomical Instrumentation (held in Marseille in June 2008). This preprint is made available with the permission of SPIE. Further information together with preprint containing full quality images is available at http://desweb.cosmology.uiuc.edu/wik

Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a investigation for maximising their effectiveness.We carry out a comparison between several common machine learning methods for galaxy classification (Convolutional Neural Network (CNN), K-nearest neighbour, LogisticRegression, Support Vector Machine, Random Forest, and Neural Networks) by using DarkEnergy Survey (DES) data combined with visual classifications from the Galaxy Zoo 1 project(GZ1). Our goal is to determine the optimal machine learning methods when using imaging data for galaxy classification. We show that CNN is the most successful method of these ten methods in our study. Using a sample of _2,800 galaxies with visual classification from GZ1, we reach an accuracy of _0.99 for the morphological classification of Ellipticals and Spirals. The further investigation of the galaxies that have a different ML and visual classification but with high predicted probabilities in our CNN usually reveals an the incorrect classification provided by GZ1. We further find the galaxies having a low probability of being either spirals or ellipticals are visually Lenticulars (S0), demonstrating that supervised learning is able to rediscover that this class of galaxy is distinct from both Es and Spirals.We confirm that _2.5% galaxies are misclassified by GZ1 in our study. After correcting these galaxies’ labels, we improve our CNN performance to an average accuracy of over 0.99 (accuracy of 0.994 is our best result)

The Dark Energy Survey Data Processing and Calibration System

The Dark Energy Survey (DES) is a 5000 deg2 grizY survey reaching characteristic photometric depths of 24th magnitude (10 sigma) and enabling accurate photometry and morphology of objects ten times fainter than in SDSS. Preparations for DES have included building a dedicated 3 deg2 CCD camera (DECam), upgrading the existing CTIO Blanco 4m telescope and developing a new high performance computing (HPC) enabled data management system (DESDM). The DESDM system will be used for processing, calibrating and serving the DES data. The total data volumes are high (~2PB), and so considerable effort has gone into designing an automated processing and quality control system. Special purpose image detrending and photometric calibration codes have been developed to meet the data quality requirements, while survey astrometric calibration, coaddition and cataloging rely on new extensions of the AstrOmatic codes which now include tools for PSF modeling, PSF homogenization, PSF corrected model fitting cataloging and joint model fitting across multiple input images. The DESDM system has been deployed on dedicated development clusters and HPC systems in the US and Germany. An extensive program of testing with small rapid turn-around and larger campaign simulated datasets has been carried out. The system has also been tested on large real datasets, including Blanco Cosmology Survey data from the Mosaic2 camera. In Fall 2012 the DESDM system will be used for DECam commissioning, and, thereafter, the system will go into full science operations.Comment: 12 pages, submitted for publication in SPIE Proceeding 8451-1

The Fifth Data Release of the Sloan Digital Sky Survey

This paper describes the Fifth Data Release (DR5) of the Sloan Digital Sky Survey (SDSS). DR5 includes all survey quality data taken through June 2005 and represents the completion of the SDSS-I project (whose successor, SDSS-II will continue through mid-2008). It includes five-band photometric data for 217 million objects selected over 8000 square degrees, and 1,048,960 spectra of galaxies, quasars, and stars selected from 5713 square degrees of that imaging data. These numbers represent a roughly 20% increment over those of the Fourth Data Release; all the data from previous data releases are included in the present release. In addition to "standard" SDSS observations, DR5 includes repeat scans of the southern equatorial stripe, imaging scans across M31 and the core of the Perseus cluster of galaxies, and the first spectroscopic data from SEGUE, a survey to explore the kinematics and chemical evolution of the Galaxy. The catalog database incorporates several new features, including photometric redshifts of galaxies, tables of matched objects in overlap regions of the imaging survey, and tools that allow precise computations of survey geometry for statistical investigations.Comment: ApJ Supp, in press, October 2007. This paper describes DR5. The SDSS Sixth Data Release (DR6) is now public, available from http://www.sdss.or

The Seventh Data Release of the Sloan Digital Sky Survey

This paper describes the Seventh Data Release of the Sloan Digital Sky Survey (SDSS), marking the completion of the original goals of the SDSS and the end of the phase known as SDSS-II. It includes 11663 deg^2 of imaging data, with most of the roughly 2000 deg^2 increment over the previous data release lying in regions of low Galactic latitude. The catalog contains five-band photometry for 357 million distinct objects. The survey also includes repeat photometry over 250 deg^2 along the Celestial Equator in the Southern Galactic Cap. A coaddition of these data goes roughly two magnitudes fainter than the main survey. The spectroscopy is now complete over a contiguous area of 7500 deg^2 in the Northern Galactic Cap, closing the gap that was present in previous data releases. There are over 1.6 million spectra in total, including 930,000 galaxies, 120,000 quasars, and 460,000 stars. The data release includes improved stellar photometry at low Galactic latitude. The astrometry has all been recalibrated with the second version of the USNO CCD Astrograph Catalog (UCAC-2), reducing the rms statistical errors at the bright end to 45 milli-arcseconds per coordinate. A systematic error in bright galaxy photometr is less severe than previously reported for the majority of galaxies. Finally, we describe a series of improvements to the spectroscopic reductions, including better flat-fielding and improved wavelength calibration at the blue end, better processing of objects with extremely strong narrow emission lines, and an improved determination of stellar metallicities. (Abridged)Comment: 20 pages, 10 embedded figures. Accepted to ApJS after minor correction

Dust Reverberation Mapping in Distant Quasars from Optical and Mid-Infrared Imaging Surveys

The size of the dust torus in Active Galactic Nuclei (AGN) and their high-luminosity counterparts, quasars, can be inferred from the time delay between UV/optical accretion disk continuum variability and the response in the mid-infrared (MIR) torus emission. This dust reverberation mapping (RM) technique has been successfully applied to $\sim 70$ $z\lesssim 0.3$ AGN and quasars. Here we present first results of our dust RM program for distant quasars covered in the SDSS Stripe 82 region combining $\sim 20$-yr ground-based optical light curves with 10-yr MIR light curves from the WISE satellite. We measure a high-fidelity lag between W1-band (3.4 $\mu$m) and $g$ band for 587 quasars over $0.3\lesssim z\lesssim 2$ (\left\sim 0.8) and two orders of magnitude in quasar luminosity. They tightly follow (intrinsic scatter $\sim 0.17$ dex in lag) the IR lag-luminosity relation observed for $z<0.3$ AGN, revealing a remarkable size-luminosity relation for the dust torus over more than four decades in AGN luminosity, with little dependence on additional quasar properties such as Eddington ratio and variability amplitude. This study motivates further investigations in the utility of dust RM for cosmology, and strongly endorses a compelling science case for the combined 10-yr Vera C. Rubin Observatory Legacy Survey of Space and Time (optical) and 5-yr Nancy Grace Roman Space Telescope 2$\mu$m light curves in a deep survey for low-redshift AGN dust RM with much lower luminosities and shorter, measurable IR lags. The compiled optical and MIR light curves for 7,384 quasars in our parent sample are made public with this work.Comment: Accepted for publication in Ap

The Phoenix stream : a cold stream in the southern hemisphere

We report the discovery of a stellar stream in the Dark Energy Survey Year 1 (Y1A1) data. The discovery was made through simple color–magnitude filters and visual inspection of the Y1A1 data. We refer to this new object as the Phoenix stream, after its resident constellation. After subtraction of the background stellar population we detect a clear signal of a simple stellar population. By fitting the ridge line of the stream in color–magnitude space, we find that a stellar population with age τ=11.5±0.5 Gyr and [Fe/H]<−1.6, located 17.5±0.9 kpc from the Sun, gives an adequate description of the stream stellar population. The stream is detected over an extension of 8°.1 (2.5 kpc) and has a width of ∼54 pc assuming a Gaussian profile, indicating that a globular cluster (GC) is a probable progenitor. There is no known GC within 5 kpc that is compatible with being the progenitor of the stream, assuming that the stream traces its orbit. We examined overdensities (ODs) along the stream, however, no obvious counterpart-bound stellar system is visible in the coadded images. We also find ODs along the stream that appear to be symmetrically distributed—consistent with the epicyclic OD scenario for the formation of cold streams—as well as a misalignment between the northern and southern part of stream. Despite the close proximity we find no evidence that this stream and the halo cluster NGC 1261 have a common accretion origin linked to the recently found EriPhe OD

An r -process enhanced star in the dwarf galaxy Tucana III

Chemically peculiar stars in dwarf galaxies provide a window for exploring the birth environment of stars with varying chemical enrichment. We present a chemical abundance analysis of the brightest star in the newly discovered ultra-faint dwarf galaxy candidate Tucana III. Because it is particularly bright for a star in an ultra-faint Milky Way (MW) satellite, we are able to measure the abundance of 28 elements, including 13 neutron-capture species. This star, DES J235532.66−593114.9 (DES J235532), shows a mild enhancement in neutron-capture elements associated with the r-process and can be classified as an r-I star. DES J235532 is the first r-I star to be discovered in an ultra-faint satellite, and Tuc III is the second extremely low-luminosity system found to contain rprocess enriched material, after Reticulum II. Comparison of the abundance pattern of DES J235532 with r-I and r-II stars found in other dwarf galaxies and in the MW halo suggests a common astrophysical origin for the neutron-capture elements seen in all r-process enhanced stars. We explore both internal and external scenarios for the r-process enrichment of Tuc III and show that with abundance patterns for additional stars, it should be possible to distinguish between them