Robert Brunner - University of Illinois at Urbana-Champaign

Robert Brunner
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Robert Brunner
University of Illinois at Urbana-Champaign
United States

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Astrophysics (33)
Cosmology and Nongalactic Astrophysics (12)
Instrumentation and Methods for Astrophysics (6)
Astrophysics of Galaxies (5)
Computer Science - Distributed; Parallel; and Cluster Computing (2)
Earth and Planetary Astrophysics (1)
Solar and Stellar Astrophysics (1)
Computer Science - Software Engineering (1)
Computer Science - Computers and Society (1)
Computer Science - Computer Vision and Pattern Recognition (1)
Physics - Physics Education (1)
Computer Science - Digital Libraries (1)

Publications Authored By Robert Brunner

Blue Waters is a Petascale-level supercomputer whose mission is to enable the national scientific and research community to solve "grand challenge" problems that are orders of magnitude more complex than can be carried out on other high performance computing systems. Given the important and unique role that Blue Waters plays in the U.S. Read More

Most existing star-galaxy classifiers use the reduced summary information from catalogs, requiring careful feature extraction and selection. The latest advances in machine learning that use deep convolutional neural networks allow a machine to automatically learn the features directly from data, minimizing the need for input from human experts. We present a star-galaxy classification framework that uses deep convolutional neural networks (ConvNets) directly on the reduced, calibrated pixel values. Read More

We describe an introductory data science course, entitled Introduction to Data Science, offered at the University of Illinois at Urbana-Champaign. The course introduced general programming concepts by using the Python programming language with an emphasis on data preparation, processing, and presentation. The course had no prerequisites, and students were not expected to have any programming experience. Read More

The Third Reference Catalogue of Bright Galaxies (RC3) is a reasonably complete listing of 23,011 nearby, large, bright galaxies. By using the final imaging data release from the Sloan Digital Sky Survey, we generate scientifically-calibrated FITS mosaics by using the montage program for all SDSS imaging bands for all RC3 galaxies that lie within the survey footprint. We further combine the SDSS g, r, and i band FITS mosaics for these galaxies to create color-composite images by using the STIFF program. Read More

We extend a machine learning (ML) framework presented previously to model galaxy formation and evolution in a hierarchical universe using N-body + hydrodynamical simulations. In this work, we show that ML is a promising technique to study galaxy formation in the backdrop of a hydrodynamical simulation. We use the Illustris Simulation to train and test various sophisticated machine learning algorithms. Read More

We present a new exploratory framework to model galaxy formation and evolution in a hierarchical universe by using machine learning (ML). Our motivations are two-fold: (1) presenting a new, promising technique to study galaxy formation, and (2) quantitatively analyzing the extent of the influence of dark matter halo properties on galaxies in the backdrop of semi-analytical models (SAMs). We use the influential Millennium Simulation and the corresponding Munich SAM to train and test various sophisticated machine learning algorithms (k-Nearest Neighbors, decision trees, random forests and extremely randomized trees). Read More

There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a more robust star-galaxy classification. To demonstrate this hybrid, ensemble approach, we combine a purely morphological classifier, a supervised machine learning method based on random forest, an unsupervised machine learning method based on self-organizing maps, and a hierarchical Bayesian template fitting method. Read More

We present the results from a time domain study of absorption lines detected in quasar spectra with repeat observations from the Sloan Digital Sky Survey Data Release 7 (SDSS DR7). Beginning with over 4500 unique time separation baselines of various absorption line species identified in the SDSS DR7 quasar spectra, we create a catalogue of 2522 quasar absorption line systems with two to eight repeat observations, representing the largest collection of unbiased and homogeneous multi-epoch absorption systems ever published. To investigate these systems for time variability of narrow absorption lines, we refine this sample based on the reliability of the system detection, the proximity of pixels with bright sky contamination to individual absorption lines, and the quality of the continuum fit. Read More

Progress is being made in code discoverability and preservation, but as discussed at ADASS XXI, many codes still remain hidden from public view. With the Astrophysics Source Code Library (ASCL) now indexed by the SAO/NASA Astrophysics Data System (ADS), the introduction of a new journal, Astronomy & Computing, focused on astrophysics software, and the increasing success of education efforts such as Software Carpentry and SciCoder, the community has the opportunity to set a higher standard for its science by encouraging the release of software for examination and possible reuse. We assembled representatives of the community to present issues inhibiting code release and sought suggestions for tackling these factors. Read More

We use a quadratic estimator with KL-compression to calculate the angular power spectrum of a volume-limited Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) galaxy sample out to l = 200. We also determine the angular power spectrum of selected subsamples with photometric redshifts z < 0.3 and 0. Read More

We calculate the angular power spectrum of galaxies selected from the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) by using a quadratic estimation method with KL-compression. The primary data sample includes over 18 million galaxies covering more than 5,700 square degrees after masking areas with bright objects, reddening greater than 0.2 magnitudes, and seeing of more than 1. Read More

We measure the angular auto-correlation functions (w) of SDSS galaxies selected to have photometric redshifts 0.1 < z < 0.4 and absolute r-band magnitudes Mr < -21. Read More

Authors: LSST Science Collaboration, Paul A. Abell1, Julius Allison2, Scott F. Anderson3, John R. Andrew4, J. Roger P. Angel5, Lee Armus6, David Arnett7, S. J. Asztalos8, Tim S. Axelrod9, Stephen Bailey10, D. R. Ballantyne11, Justin R. Bankert12, Wayne A. Barkhouse13, Jeffrey D. Barr14, L. Felipe Barrientos15, Aaron J. Barth16, James G. Bartlett17, Andrew C. Becker18, Jacek Becla19, Timothy C. Beers20, Joseph P. Bernstein21, Rahul Biswas22, Michael R. Blanton23, Joshua S. Bloom24, John J. Bochanski25, Pat Boeshaar26, Kirk D. Borne27, Marusa Bradac28, W. N. Brandt29, Carrie R. Bridge30, Michael E. Brown31, Robert J. Brunner32, James S. Bullock33, Adam J. Burgasser34, James H. Burge35, David L. Burke36, Phillip A. Cargile37, Srinivasan Chandrasekharan38, George Chartas39, Steven R. Chesley40, You-Hua Chu41, David Cinabro42, Mark W. Claire43, Charles F. Claver44, Douglas Clowe45, A. J. Connolly46, Kem H. Cook47, Jeff Cooke48, Asantha Cooray49, Kevin R. Covey50, Christopher S. Culliton51, Roelof de Jong52, Willem H. de Vries53, Victor P. Debattista54, Francisco Delgado55, Ian P. Dell'Antonio56, Saurav Dhital57, Rosanne Di Stefano58, Mark Dickinson59, Benjamin Dilday60, S. G. Djorgovski61, Gregory Dobler62, Ciro Donalek63, Gregory Dubois-Felsmann64, Josef Durech65, Ardis Eliasdottir66, Michael Eracleous67, Laurent Eyer68, Emilio E. Falco69, Xiaohui Fan70, Christopher D. Fassnacht71, Harry C. Ferguson72, Yanga R. Fernandez73, Brian D. Fields74, Douglas Finkbeiner75, Eduardo E. Figueroa76, Derek B. Fox77, Harold Francke78, James S. Frank79, Josh Frieman80, Sebastien Fromenteau81, Muhammad Furqan82, Gaspar Galaz83, A. Gal-Yam84, Peter Garnavich85, Eric Gawiser86, John Geary87, Perry Gee88, Robert R. Gibson89, Kirk Gilmore90, Emily A. Grace91, Richard F. Green92, William J. Gressler93, Carl J. Grillmair94, Salman Habib95, J. S. Haggerty96, Mario Hamuy97, Alan W. Harris98, Suzanne L. Hawley99, Alan F. Heavens100, Leslie Hebb101, Todd J. Henry102, Edward Hileman103, Eric J. Hilton104, Keri Hoadley105, J. B. Holberg106, Matt J. Holman107, Steve B. Howell108, Leopoldo Infante109, Zeljko Ivezic110, Suzanne H. Jacoby111, Bhuvnesh Jain112, R113, Jedicke114, M. James Jee115, J. Garrett Jernigan116, Saurabh W. Jha117, Kathryn V. Johnston118, R. Lynne Jones119, Mario Juric120, Mikko Kaasalainen121, Styliani122, Kafka, Steven M. Kahn, Nathan A. Kaib, Jason Kalirai, Jeff Kantor, Mansi M. Kasliwal, Charles R. Keeton, Richard Kessler, Zoran Knezevic, Adam Kowalski, Victor L. Krabbendam, K. Simon Krughoff, Shrinivas Kulkarni, Stephen Kuhlman, Mark Lacy, Sebastien Lepine, Ming Liang, Amy Lien, Paulina Lira, Knox S. Long, Suzanne Lorenz, Jennifer M. Lotz, R. H. Lupton, Julie Lutz, Lucas M. Macri, Ashish A. Mahabal, Rachel Mandelbaum, Phil Marshall, Morgan May, Peregrine M. McGehee, Brian T. Meadows, Alan Meert, Andrea Milani, Christopher J. Miller, Michelle Miller, David Mills, Dante Minniti, David Monet, Anjum S. Mukadam, Ehud Nakar, Douglas R. Neill, Jeffrey A. Newman, Sergei Nikolaev, Martin Nordby, Paul O'Connor, Masamune Oguri, John Oliver, Scot S. Olivier, Julia K. Olsen, Knut Olsen, Edward W. Olszewski, Hakeem Oluseyi, Nelson D. Padilla, Alex Parker, Joshua Pepper, John R. Peterson, Catherine Petry, Philip A. Pinto, James L. Pizagno, Bogdan Popescu, Andrej Prsa, Veljko Radcka, M. Jordan Raddick, Andrew Rasmussen, Arne Rau, Jeonghee Rho, James E. Rhoads, Gordon T. Richards, Stephen T. Ridgway, Brant E. Robertson, Rok Roskar, Abhijit Saha, Ata Sarajedini, Evan Scannapieco, Terry Schalk, Rafe Schindler, Samuel Schmidt, Sarah Schmidt, Donald P. Schneider, German Schumacher, Ryan Scranton, Jacques Sebag, Lynn G. Seppala, Ohad Shemmer, Joshua D. Simon, M. Sivertz, Howard A. Smith, J. Allyn Smith, Nathan Smith, Anna H. Spitz, Adam Stanford, Keivan G. Stassun, Jay Strader, Michael A. Strauss, Christopher W. Stubbs, Donald W. Sweeney, Alex Szalay, Paula Szkody, Masahiro Takada, Paul Thorman, David E. Trilling, Virginia Trimble, Anthony Tyson, Richard Van Berg, Daniel Vanden Berk, Jake VanderPlas, Licia Verde, Bojan Vrsnak, Lucianne M. Walkowicz, Benjamin D. Wandelt, Sheng Wang, Yun Wang, Michael Warner, Risa H. Wechsler, Andrew A. West, Oliver Wiecha, Benjamin F. Williams, Beth Willman, David Wittman, Sidney C. Wolff, W. Michael Wood-Vasey, Przemek Wozniak, Patrick Young, Andrew Zentner, Hu Zhan
Affiliations: 1Stella, 2Stella, 3Stella, 4Stella, 5Stella, 6Stella, 7Stella, 8Stella, 9Stella, 10Stella, 11Stella, 12Stella, 13Stella, 14Stella, 15Stella, 16Stella, 17Stella, 18Stella, 19Stella, 20Stella, 21Stella, 22Stella, 23Stella, 24Stella, 25Stella, 26Stella, 27Stella, 28Stella, 29Stella, 30Stella, 31Stella, 32Stella, 33Stella, 34Stella, 35Stella, 36Stella, 37Stella, 38Stella, 39Stella, 40Stella, 41Stella, 42Stella, 43Stella, 44Stella, 45Stella, 46Stella, 47Stella, 48Stella, 49Stella, 50Stella, 51Stella, 52Stella, 53Stella, 54Stella, 55Stella, 56Stella, 57Stella, 58Stella, 59Stella, 60Stella, 61Stella, 62Stella, 63Stella, 64Stella, 65Stella, 66Stella, 67Stella, 68Stella, 69Stella, 70Stella, 71Stella, 72Stella, 73Stella, 74Stella, 75Stella, 76Stella, 77Stella, 78Stella, 79Stella, 80Stella, 81Stella, 82Stella, 83Stella, 84Stella, 85Stella, 86Stella, 87Stella, 88Stella, 89Stella, 90Stella, 91Stella, 92Stella, 93Stella, 94Stella, 95Stella, 96Stella, 97Stella, 98Stella, 99Stella, 100Stella, 101Stella, 102Stella, 103Stella, 104Stella, 105Stella, 106Stella, 107Stella, 108Stella, 109Stella, 110Stella, 111Stella, 112Stella, 113Stella, 114Stella, 115Stella, 116Stella, 117Stella, 118Stella, 119Stella, 120Stella, 121Stella, 122Stella

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9. Read More

We measure the angular 2-point correlation functions of galaxies in a volume limited, photometrically selected galaxy sample from the fifth data release of the Sloan Digital Sky Survey. We split the sample both by luminosity and galaxy type and use a halo-model analysis to find halo-occupation distributions that can simultaneously model the clustering of all, early-, and late-type galaxies in a given sample. Our results for the full galaxy sample are generally consistent with previous results using the SDSS spectroscopic sample, taking the differences between the median redshifts of the photometric and spectroscopic samples into account. Read More

Affiliations: 1Herzberg Institute of Astrophysics, Victoria, BC, Canada, 2Department of Astronomy, University of Illinois at Urbana-Champaign

We review the current state of data mining and machine learning in astronomy. 'Data Mining' can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding the potential to fully exploit the exponentially increasing amount of available data, promising great scientific advance. Read More

Affiliations: 1The Pennsylvania State University, 2Princeton, 3Princeton, 4The Pennsylvania State University, 5University of Washington, 6Drexel University, 7The Pennsylvania State University, 8Ohio State University, 9York University, 10Princeton, 11University of Illinois at Urbana-Champaign

We present measurements of the quasar two-point correlation function, \xi_{Q}, over the redshift range z=0.3-2.2 based upon data from the SDSS. Read More

We analyze the cross-correlation of 2,705 unambiguously intervening Mg II (2796,2803A) quasar absorption line systems with 1,495,604 luminous red galaxies (LRGs) from the Fifth Data Release of the Sloan Digital Sky Survey within the redshift range 0.36<=z<=0.8. Read More

Affiliations: 1University of Sydney, 2Drexel, 3Durham, 4ATNF, 5Anglo-Australian Observatory, 6University of Sydney, 7Anglo-Australian Observatory, 8University of Illinois at Urbana-Champaign, 9Anglo-Australian Observatory, 10Portsmouth, 11Exeter, 12Anglo-Australian Observatory, 13Swinburne, 14CTIO, 15Queensland, 16Durham, 17University of Sydney, 18Sussex, 19Oxford, 20University of Illinois at Urbana-Champaign, 21Portsmouth, 22Durham, 23Queensland, 24Queensland, 25Durham, 26Penn State, 27Wyoming, 28FermiLab, 29Princeton, 30Durham
Category: Astrophysics

We present the final spectroscopic QSO catalogue from the 2dF-SDSS LRG and QSO (2SLAQ) Survey. This is a deep, 18Read More

Using a homogenous sample of 38,208 quasars with a sky coverage of $4000 {\rm deg^2}$ drawn from the SDSS Data Release Five quasar catalog, we study the dependence of quasar clustering on luminosity, virial black hole mass, quasar color, and radio loudness. At $z<2.5$, quasar clustering depends weakly on luminosity and virial black hole mass, with typical uncertainty levels $\sim 10%$ for the measured correlation lengths. Read More

Affiliations: 1Drexel University, 2Drexel University, 3Spitzer Science Center, 4University of Illinois, 5University of Portsmouth, 6Institute for Advanced Study, 7University of Illinois, 8Penn State University, 9Georgia Tech, 10Drexel University, 11Johns Hopkins University, 12Penn State University, 13Spitzer Science Center, 14Johns Hopkins University
Category: Astrophysics

We explore the multidimensional, multiwavelength selection of quasars from mid-IR (MIR) plus optical data, specifically from Spitzer-IRAC and the Sloan Digital Sky Survey (SDSS). We apply modern statistical techniques to combined Spitzer MIR and SDSS optical data, allowing up to 8-D color selection of quasars. Using a Bayesian selection method, we catalog 5546 quasar candidates to an 8. Read More

Affiliations: 1Drexel University, 2University of Illinois, 3Georgia Tech, 4Georgia Tech, 5University of Portsmouth, 6University of Illinois, 7John Hopkins University, 8Penn State University, 9University of Washington
Category: Astrophysics

We present a catalog of 1,172,157 quasar candidates selected from the photometric imaging data of the Sloan Digital Sky Survey (SDSS). The objects are all point sources to a limiting magnitude of i=21.3 from 8417 sq. Read More


This paper provides an evaluation of SGI RASCTM RC100 technology from a computational science software developer's perspective. A brute force implementation of a two-point angular correlation function is used as a test case application. The computational kernel of this test case algorithm is ported to the Mitrion-C programming language and compiled, targeting the RC100 hardware. Read More

We present a novel technique to measure $\sigma_8$, by measuring the dependence of the second-order bias of a density field on $\sigma_8$ using two separate techniques. Each technique employs area-averaged angular correlation functions ($\bar{\omega}_N$), one relying on the shape of $\bar{\omega}_2$, the other relying on the amplitude of $s_3$ ($s_3 =\bar{\omega}_3/\bar{\omega}_2^2$). We confirm the validity of the method by testing it on a mock catalog drawn from Millennium Simulation data and finding $\sigma_8^{measured}- \sigma_8^{true} = -0. Read More

Affiliations: 1Department of Astronomy, University of Illinois at Urbana-Champaign, 2Department of Astronomy, University of Illinois at Urbana-Champaign, 3Department of Astronomy, University of Illinois at Urbana-Champaign, 4Department of Physics, University of Illinois at Urbana-Champaign, 5Department of Astronomy, University of Illinois at Urbana-Champaign, 6National Center for Supercomputing Applications
Category: Astrophysics

We apply machine learning in the form of a nearest neighbor instance-based algorithm (NN) to generate full photometric redshift probability density functions (PDFs) for objects in the Fifth Data Release of the Sloan Digital Sky Survey (SDSS DR5). We use a conceptually simple but novel application of NN to generate the PDFs - perturbing the object colors by their measurement error - and using the resulting instances of nearest neighbor distributions to generate numerous individual redshifts. When the redshifts are compared to existing SDSS spectroscopic data, we find that the mean value of each PDF has a dispersion between the photometric and spectroscopic redshift consistent with other machine learning techniques, being sigma = 0. Read More

Affiliations: 1Department of Astronomy, University of Illinois at Urbana-Champaign, 2Department of Astronomy, University of Illinois at Urbana-Champaign, 3Department of Astronomy, University of Illinois at Urbana-Champaign

We present recent results from the LCDM (Laboratory for Cosmological Data Mining; http://lcdm.astro.uiuc. Read More

We explore how the local environment is related to the redshift, type, and luminosity of active galactic nuclei (AGN). Recent simulations and observations are converging on the view that the extreme luminosity of quasars is fueled in major mergers of gas-rich galaxies. In such a picture, quasars are expected to be located in regions with a higher density of galaxies on small scales where mergers are more likely to take place. Read More

The objective of our research is to demonstrate the practical usage and orders of magnitude speedup of real-world applications by using alternative technologies to support high performance computing. Currently, the main barrier to the widespread adoption of this technology is the lack of development tools and case studies that typically impede non-specialists that might otherwise develop applications that could leverage these technologies. By partnering with the Innovative Systems Laboratory at the National Center for Supercomputing, we have obtained access to several novel technologies, including several Field-Programmable Gate Array (FPGA) systems, NVidia Graphics Processing Units (GPUs), and the STI Cell BE platform. Read More

Angular power spectra are an important measure of the angular clustering of a given distribution. In Cosmology, they are applied to such vastly different observations as galaxy surveys that cover a fraction of the sky and the Cosmic Microwave Background that covers the entire sky, to obtain fundamental parameters that determine the structure and evolution of the universe. The calculation of an angular power spectrum, however, is complex and the optimization of these calculations is a necessary consideration for current and forthcoming observational surveys. Read More


In this case study, we investigate the impact of workload balance on the performance of multi-FPGA codes. We start with an application in which two distinct kernels run in parallel on two SRC-6 MAP processors. We observe that one of the MAP processors is idle 18% of the time while the other processor is fully utilized. Read More

Affiliations: 1University of Illinois at Urbana-Champaign, National Center for Supercomputing Applications, 2University of Illinois at Urbana-Champaign, National Center for Supercomputing Applications, 3University of Illinois at Urbana-Champaign, National Center for Supercomputing Applications
Category: Astrophysics

We present recent results from the Laboratory for Cosmological Data Mining (http://lcdm.astro.uiuc. Read More

We present spectroscopy of binary quasar candidates selected from Data Release 4 of the Sloan Digital Sky Survey (SDSS DR4) using Kernel Density Estimation (KDE). We present 27 new sets of observations, 10 of which are binary quasars, roughly doubling the number of known $g < 21$ binaries with component separations of 3 to 6". Only 3 of 49 spectroscopically identified objects are non-quasars, confirming that the quasar selection efficiency of the KDE technique is $\sim95$%. Read More

We present cosmological results from the statistics of lensed quasars in the Sloan Digital Sky Survey (SDSS) Quasar Lens Search. By taking proper account of the selection function, we compute the expected number of quasars lensed by early-type galaxies and their image separation distribution assuming a flat universe, which is then compared with 7 lenses found in the SDSS Data Release 3 to derive constraints on dark energy under strictly controlled criteria. For a cosmological constant model (w=-1) we obtain \Omega_\Lambda=0. Read More

We present estimates of the N-point galaxy, area-averaged, angular correlation functions $\bar{\omega}_{N}$($\theta$) for $N$ = 2,... Read More

Affiliations: 1Department of Astronomy, University of Illinois at Urbana-Champaign, 2Department of Astronomy, University of Illinois at Urbana-Champaign, 3Department of Astronomy, University of Illinois at Urbana-Champaign, 4Department of Physics, University of Illinois at Urbana-Champaign, 5Department of Astronomy, University of Illinois at Urbana-Champaign, 6National Center for Supercomputing Applications, 7National Center for Supercomputing Applications
Category: Astrophysics

We apply instance-based machine learning in the form of a k-nearest neighbor algorithm to the task of estimating photometric redshifts for 55,746 objects spectroscopically classified as quasars in the Fifth Data Release of the Sloan Digital Sky Survey. We compare the results obtained to those from an empirical color-redshift relation (CZR). In contrast to previously published results using CZRs, we find that the instance-based photometric redshifts are assigned with no regions of catastrophic failure. Read More

Using ~300,000 photometrically classified quasars, by far the largest quasar sample ever used for such analyses, we study the redshift and luminosity evolution of quasar clustering on scales of ~50 kpc/h to ~20 Mpc/h from redshifts of z~0.75 to z~2.28. Read More


We study quasar clustering on small scales, modeling clustering amplitudes using halo-driven dark matter descriptions. From 91 pairs on scales <35 kpc/h, we detect only a slight excess in quasar clustering over our best-fit large-scale model. Integrated across all redshifts, the implied quasar bias is b_Q = 4. Read More

We present a time-variability analysis of 29 broad absorption line quasars (BALQSOs) observed in two epochs by the Sloan Digital Sky Survey (SDSS). These spectra are selected from a larger sample of BALQSOs with multiple observations by virtue of exhibiting a broad CIV $\lambda$1549 absorption trough separated from the rest frame of the associated emission peak by more than 3600 km s$^{-1}$. Detached troughs facilitate higher precision variability measurements, since the measurement of the absorption in these objects is not complicated by variation in the emission line flux. Read More

Affiliations: 1University of Illinois at Urbana-Champaign, 2University of Sussex, 3University of Illinois at Urbana-Champaign
Category: Astrophysics

We use the Fourth Data Release of the Sloan Digital Sky Survey to investigate the relation between galaxy rest frame u-r colour, morphology, as described by the concentration and Sersic indices, and environmental density, for a sample of 79,553 galaxies at z < ~0.1. We split the samples according to density and luminosity and recover the expected bimodal distribution in the colour-morphology plane, shown especially clearly by this subsampling. Read More

Affiliations: 1ICG, Portsmouth, 2ICG, 3ICG, 4UPitt, 5JHU, 6Illinois, 7Illinois, 8Georgia Tech, 9UPitt, 10Penn State
Category: Astrophysics

We present evidence of a large angle correlation between the cosmic microwave background measured by WMAP and a catalog of photometrically detected quasars from the SDSS. The observed cross correlation is (0.30 +- 0. Read More

Affiliations: 1University of Illinois at Urbana-Champaign, 2University of Illinois at Urbana-Champaign, 3University of Illinois at Urbana-Champaign, 4National Center for Supercomputing Applications
Category: Astrophysics

We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that these star/galaxy classifications are expected to be reliable for approximately 22 million objects with r < ~20. The general machine learning environment Data-to-Knowledge and supercomputing resources enabled extensive investigation of the decision tree parameter space. Read More

With close pairs of quasars at different redshifts, a background quasar sightline can be used to study a foreground quasar's environment in absorption. We search 149 moderate resolution background quasar spectra, from Gemini, Keck, the MMT, and the SDSS to survey Lyman Limit Systems (LLSs) and Damped Ly-alpha systems (DLAs) in the vicinity of 1.8 < z < 4. Read More

We determine the number counts and z=0-5 luminosity function for a well-defined, homogeneous sample of quasars from the Sloan Digital Sky Survey (SDSS). We conservatively define the most uniform statistical sample possible, consisting of 15,343 quasars within an effective area of 1622 deg^2 that was derived from a parent sample of 46,420 spectroscopically confirmed broad-line quasars in the 5282 deg^2 of imaging data from SDSS Data Release Three. The sample extends from i=15 to i=19. Read More

We present variability and multi-wavelength photometric information for the 933 known quasars in the QUEST Variability Survey. These quasars are grouped into variable and non-variable populations based on measured variability confidence levels. In a time-limited synoptic survey, we detect an anti-correlation between redshift and the likelihood of variability. Read More

We present new measurements of the quasar autocorrelation from a sample of \~80,000 photometrically-classified quasars taken from SDSS DR1. We find a best-fit model of $\omega(\theta) = (0.066\pm^{0. Read More

Affiliations: 1National Center for Supercomputing Applications, 2National Center for Supercomputing Applications, 3National Center for Supercomputing Applications
Category: Astrophysics

Advanced instruments in a variety of scientific domains are collecting massive amounts of data that must be post-processed and organized to support scientific research activities. Astronomers have been pioneers in the use of databases to host highly structured repositories of sky survey data. As more powerful telescopes come online, the increased volume and complexity of the data collected poses enormous challenges to state-of-the-art database systems and data-loading techniques. Read More

Affiliations: 1University of Illinois at Urbana-Champaign, 2University of Sussex, 3University of Illinois at Urbana-Champaign, 4Liverpool John Moores University, 5Apache Point Observatory
Category: Astrophysics

Bivariate luminosity functions (LFs) are computed for galaxies in the New York Value-Added Galaxy Catalogue, based on the Sloan Digital Sky Survey Data Release 4. The galaxy properties investigated are the morphological type, inverse concentration index, Sersic index, absolute effective surface brightness, reference frame colours, absolute radius, eClass spectral type, stellar mass and galaxy environment. The morphological sample is flux-limited to galaxies with r < 15. Read More

We present a sample of 218 new quasar pairs with proper transverse separations R_prop < 1 Mpc/h over the redshift range 0.5 < z < 3.0, discovered from an extensive follow up campaign to find companions around the Sloan Digital Sky Survey and 2dF Quasar Redshift Survey quasars. Read More