arXiv subjects

Robert J. Brunner

Publications and source records attributed to Robert J. Brunner.

At least 37 records · Page 2Linked to original sources

arXiv2008

Efficient Photometric Selection of Quasars from the Sloan Digital Sky Survey: II. ~1,000,000 Quasars from Data Release Six

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. deg. of imaging from SDSS Data Release 6 (DR6). This sample extends our previous catalog by using the latest SDSS public release data and probing both UV-excess and high-redshift quasars. While the addition of high-redshift candidates reduces the overall efficiency (quasars:quasar candidates) of the catalog to ~80%, it is expected to contain no fewer than 850,000 bona fide quasars -- ~8 times the number of our previous sample, and ~10 times the size of the largest spectroscopic quasar catalog. Cross-matching between our photometric catalog and spectroscopic quasar catalogs from both the SDSS and 2dF Surveys, yields 88,879 spectroscopically confirmed quasars. For judicious selection of the most robust UV-excess sources (~500,000 objects in all), the efficiency is nearly 97% -- more than sufficient for detailed statistical analyses. The catalog's completeness to type 1 (broad-line) quasars is expected to be no worse than 70%, with most missing objects occurring at z<0.7 and 2.5<z<3.0. In addition to classification information, we provide photometric redshift estimates (typically good to Delta z +/- 0.3 [2 sigma]) and cross-matching with radio, X-ray, and proper motion catalogs. Finally, we consider the catalog's utility for determining the optical luminosity function of quasars and are able to confirm the flattening of the bright-end slope of the quasar luminosity function at z~4 as compared to z~2.

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arXiv2008

AGN Environments in the Sloan Digital Sky Survey I: Dependence on Type, Redshift, and Luminosity

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. However, in this picture, the activity observed in low-luminosity AGN is due to secular processes that are less dependent on the local galaxy density. To test this hypothesis, we compare the local photometric galaxy density on kiloparsec scales around spectroscopic Type I and Type II quasars to the local density around lower luminosity spectroscopic Type I and Type II AGN. To minimize projection effects and evolution in the photometric galaxy sample we use to characterize AGN environments, we place our random control sample at the same redshift as our AGN and impose a narrow redshift window around both the AGN and control targets. We find that higher luminosity AGN have more overdense environments compared to lower luminosity AGN on all scales out to our $2\Mpchseventy$ limit. Additionally, in the range $0.3\leqslant z\leqslant 0.6$, Type II quasars have similarly overdense environments to those of bright Type I quasars on all scales out to our $2\Mpchseventy$ limit, while the environment of dimmer Type I quasars appears to be less overdense than the environment of Type II quasars. We see increased overdensity for Type II AGN compared to Type I AGN on scales out to our limit of $2\Mpchseventy$ in overlapping redshift ranges. We also detect marginal evidence for evolution in the number of galaxies within $2\Mpchseventy$ of a quasar with redshift.

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arXiv2008

Mitrion-C Application Development on SGI Altix 350/RC100

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. We explore several code optimization techniques and report performance results for different designs. We conclude the paper with an analysis of this system based on our observations while implementing the test case. Overall, the hardware platform and software development tools were found to be satisfactory for accelerating computationally intensive applications, however, several system improvements are desirable.

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arXiv2008

Robust Machine Learning Applied to Terascale Astronomical Datasets

We present recent results from the LCDM (Laboratory for Cosmological Data Mining; http://lcdm.astro.uiuc.edu) collaboration between UIUC Astronomy and NCSA to deploy supercomputing cluster resources and machine learning algorithms for the mining of terascale astronomical datasets. This is a novel application in the field of astronomy, because we are using such resources for data mining, and not just performing simulations. Via a modified implementation of the NCSA cyberenvironment Data-to-Knowledge, we are able to provide improved classifications for over 100 million stars and galaxies in the Sloan Digital Sky Survey, improved distance measures, and a full exploitation of the simple but powerful k-nearest neighbor algorithm. A driving principle of this work is that our methods should be extensible from current terascale datasets to upcoming petascale datasets and beyond. We discuss issues encountered to-date, and further issues for the transition to petascale. In particular, disk I/O will become a major limiting factor unless the necessary infrastructure is implemented.

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arXiv2008

Normalization of the Matter Power Spectrum via Higher-Order Angular Correlations of Luminous Red Galaxies

We present a novel technique to measure $σ_8$, by measuring the dependence of the second-order bias of a density field on $σ_8$ using two separate techniques. Each technique employs area-averaged angular correlation functions ($\barω_N$), one relying on the shape of $\barω_2$, the other relying on the amplitude of $s_3$ ($s_3 =\barω_3/\barω_2^2$). We confirm the validity of the method by testing it on a mock catalog drawn from Millennium Simulation data and finding $σ_8^{measured}- σ_8^{true} = -0.002 \pm 0.062$. We create a catalog of photometrically selected LRGs from SDSS DR5 and separate it into three distinct data sets by photometric redshift, with median redshifts of 0.47, 0.53, and 0.61. Measurements of $c_2$, and $σ_8$ are made for each data set, assuming flat geometry and WMAP3 best-fit priors on $Ω_m$, $h$, and $Γ$. We find, with increasing redshfit, $c_2 = 0.09 \pm 0.04$, $0.09 \pm 0.05$, and $0.09 \pm 0.03$ and $σ_8 = 0.78 \pm 0.08$, $0.80 \pm 0.09$, and $0.80 \pm 0.09$. We combine these three consistent $σ_8$ measurements to produce the result $σ_8 = 0.79 \pm 0.05$. Allowing the parameters $Ω_m$, $h$, and $Γ$ to vary within their WMAP3 1$σ$ error, we find that the best-fit $σ_8$ does not change by more than 8% and we are thus confident our measurement is accurate to within 10%. We anticipate that future surveys, such as Pan-STARRS, DES, and LSST, will be able to employ this method to measure $σ_8$ to great precision, and will serve as an important check, complementary, on the values determined via more established methods.

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arXiv2008

Robust Machine Learning Applied to Astronomical Datasets III: Probabilistic Photometric Redshifts for Galaxies and Quasars in the SDSS and GALEX

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 = 0.0207 +/- 0.0001 for main sample galaxies to r < 17.77 mag, sigma = 0.0243 +/- 0.0002 for luminous red galaxies to r < ~19.2 mag, and sigma = 0.343 +/- 0.005 for quasars to i < 20.3 mag. The PDFs allow the selection of subsets with improved statistics. For quasars, the improvement is dramatic: for those with a single peak in their probability distribution, the dispersion is reduced from 0.343 to sigma = 0.117 +/- 0.010, and the photometric redshift is within 0.3 of the spectroscopic redshift for 99.3 +/- 0.1% of the objects. Thus, for this optical quasar sample, we can virtually eliminate 'catastrophic' photometric redshift estimates. In addition to the SDSS sample, we incorporate ultraviolet photometry from the Third Data Release of the Galaxy Evolution Explorer All-Sky Imaging Survey (GALEX AIS GR3) to create PDFs for objects seen in both surveys. For quasars, the increased coverage of the observed frame UV of the SED results in significant improvement over the full SDSS sample, with sigma = 0.234 +/- 0.010. We demonstrate that this improvement is genuine. [Abridged]

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arXiv2007

Developing and Deploying Advanced Algorithms to Novel Supercomputing Hardware

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. Our goal is to not only demonstrate the capabilities of these systems, but to also serve as guides for others to follow in our path. To date, we have explored the efficacy of the SRC-6 MAP-C and MAP-E and SGI RASC Athena and RC100 reconfigurable computing platforms in supporting a two-point correlation function which is used in a number of different scientific domains. In a brute force test, the FPGA based single-processor system has achieved an almost two orders of magnitude speedup over a single-processor CPU system. We are now developing implementations of this algorithm on other platforms, including one using a GPU. Given the considerable efforts of the cosmology community in optimizing these classes of algorithms, we are currently working to implement an optimized version of the basic family of correlation functions by using tree-based data structures. Finally, we are also exploring other algorithms, such as instance-based classifiers, power spectrum estimators, and higher-order correlation functions that are also commonly used in a wide range of scientific disciplines.

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arXiv2007

Dynamic load-balancing on multi-FPGA systems: a case study

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. We investigate a task redistribution schema which serializes the execution of the two kernels, yet parallelizes execution of each individual kernel by spreading the workload between two MAP processors. This implementation results in a near 100% utilization of both MAP processors and the overall application performance is improved by 9%.

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arXiv2007

The Sloan Digital Sky Survey Quasar Lens Search. II. Statistical Lens Sample from the Third Data Release

We report the first results of our systematic search for strongly lensed quasars using the spectroscopically confirmed quasars in the Sloan Digital Sky Survey (SDSS). Among 46,420 quasars from the SDSS Data Release 3 (~4188 deg^2), we select a subsample of 22,683 quasars that are located at redshifts between 0.6 and 2.2 and are brighter than the Galactic extinction corrected i-band magnitude of 19.1. We identify 220 lens candidates from the quasar subsample, for which we conduct extensive and systematic follow-up observations in optical and near-infrared wavebands, in order to construct a complete lensed quasar sample at image separations between 1'' and 20'' and flux ratios of faint to bright lensed images larger than 10^{-0.5}. We construct a statistical sample of 11 lensed quasars. Ten of these are galaxy-scale lenses with small image separations (~1''-2'') and one is a large separation (15'') system which is produced by a massive cluster of galaxies, representing the first statistical sample of lensed quasars including both galaxy- and cluster-scale lenses. The Data Release 3 spectroscopic quasars contain an additional 11 lensed quasars outside the statistical sample.

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arXiv2007

The Sloan Digital Sky Survey Quasar Lens Search. III. Constraints on Dark Energy from the Third Data Release Quasar Lens Catalog

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 Ω_Λ=0.74^{+0.11}_{-0.15}(stat.)^{+0.13}_{-0.06}(syst.). Allowing w to be a free parameter we find Ω_M=0.26^{+0.07}_{-0.06}(stat.)^{+0.03}_{-0.05}(syst.) and w=-1.1\pm0.6(stat.)^{+0.3}_{-0.5}(syst.) when combined with the constraint from the measurement of baryon acoustic oscillations in the SDSS luminous red galaxy sample. Our results are in good agreement with earlier lensing constraints obtained using radio lenses, and provide additional confirmation of the presence of dark energy consistent with a cosmological constant, derived independently of type Ia supernovae.

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arXiv2007

Robust Machine Learning Applied to Terascale Astronomical Datasets

We present recent results from the Laboratory for Cosmological Data Mining (http://lcdm.astro.uiuc.edu) at the National Center for Supercomputing Applications (NCSA) to provide robust classifications and photometric redshifts for objects in the terascale-class Sloan Digital Sky Survey (SDSS). Through a combination of machine learning in the form of decision trees, k-nearest neighbor, and genetic algorithms, the use of supercomputing resources at NCSA, and the cyberenvironment Data-to-Knowledge, we are able to provide improved classifications for over 100 million objects in the SDSS, improved photometric redshifts, and a full exploitation of the powerful k-nearest neighbor algorithm. This work is the first to apply the full power of these algorithms to contemporary terascale astronomical datasets, and the improvement over existing results is demonstrable. We discuss issues that we have encountered in dealing with data on the terascale, and possible solutions that can be implemented to deal with upcoming petascale datasets.

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arXiv2007

Galaxy Colour, Morphology, and Environment in the Sloan Digital Sky Survey

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. We quantify the bimodality by a sum of two Gaussians on the colour and morphology axes and show that, for the red/early-type population both colour and morphology do not change significantly as a function of density. For the blue/late-type population, with increasing density the colour becomes redder but the morphology again does not change significantly. Both populations become monotonically redder and of earlier type with increasing luminosity. There is no significant qualitative difference between the behaviour of the two morphological measures. We supplement the morphological sample with 13,655 galaxies assigned Hubble types by an artificial neural network. We find, however, that the resulting distribution is less well described by two Gaussians. Therefore, there are either more than two significant morphological populations, physical processes not seen in colour space, or the Hubble type, particularly the different subtypes of spirals Sa-Sd, has an irreducible fuzziness when related to environmental density. For each of the three measures of morphology, on removing the density relation due to it, we recover a strong residual relation in colour. However, on similarly removing the colour-density relation there is no evidence for a residual relation due to morphology. [Abridged]

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arXiv2007

Quasar Clustering at $25\kpch$ from a Complete Sample of Binaries

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 $\sim95$%. Several of our observed binaries are wide-separation lens candidates that merit additional higher-resolution observations. One interesting pair may be an M star binary, or an M star-binary quasar superposition. Our candidates are initially selected by UV-excess ($u-g < 1$), but are otherwise selected irrespective of the relative colors of the quasar pair, and we thus use them to suggest optimal color similarity and photometric redshift approaches for targeting binary quasars, or projected quasar pairs. From a sample that is complete on proper scales of $23.7 < R_{prop} < 29.7\kpch$, we determine the projected quasar correlation function to be $W_p=24.0 \pm^{16.9}_{10.8}$, which is $2σ$ lower than recent estimates. We argue that our low $W_p$ estimates may indicate redshift evolution in the quasar correlation function from $z\sim1.9$ to $z\sim1.4$ on scales of $R_{prop} \sim25\kpch$. The size of this evolution broadly tracks quasar clustering on larger scales, consistent with merger-driven models of quasar origin. Although our sample alone is insufficient to detect evolution in quasar clustering on small scales, an $i$-selected DR6 KDE quasar catalog, which will contain several hundred $z \leqsim 5$ binary quasars, could easily constrain any clustering evolution at $R_{prop} \sim25\kpch$.

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arXiv2007

Higher-Order Angular Galaxy Correlations in the SDSS: Redshift and Color Dependence of non-Linear Bias

We present estimates of the N-point galaxy, area-averaged, angular correlation functions $\barω_{N}$($θ$) for $N$ = 2,...,7 for galaxies from the fifth data release of the Sloan Digital Sky Survey. Our parent sample is selected from galaxies with $18 \leq r < 21$, and is the largest ever used to study higher-order correlations. We subdivide this parent sample into two volume limited samples using photometric redshifts, and these two samples are further subdivided by magnitude, redshift, and color (producing early- and late-type galaxy samples) to determine the dependence of $\barω_{N}$($θ$) on luminosity, redshift, and galaxy-type. We measure $\barω_{N}$($θ$) using oversampling techniques and use them to calculate the projected, $s_{N}$. Using models derived from theoretical power-spectra and perturbation theory, we measure the bias parameters $b_1$ and $c_2$, finding that the large differences in both bias parameters ($b_1$ and $c_2$) between early- and late-type galaxies are robust against changes in redshift, luminosity, and $σ_8$, and that both terms are consistently smaller for late-type galaxies. By directly comparing their higher-order correlation measurements, we find large differences in the clustering of late-type galaxies at redshifts lower than 0.3 and those at redshifts higher than 0.3, both at large scales ($c_2$ is larger by $\sim0.5$ at $z > 0.3$) and small scales (large amplitudes are measured at small scales only for $z > 0.3$, suggesting much more merger driven star formation at $z > 0.3$). Finally, our measurements of $c_2$ suggest both that $σ_8 < 0.8$ and $c_2$ is negative.

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arXiv2007

The Sloan Digital Sky Survey Quasar Catalog IV. Fifth Data Release

We present the fourth edition of the Sloan Digital Sky Survey (SDSS) Quasar Catalog. The catalog contains 77,429 objects; this is an increase of over 30,000 entries since the previous edition. The catalog consists of the objects in the SDSS Fifth Data Release that have luminosities larger than M_i = -22.0 (in a cosmology with H_0 = 70 km/s/Mpc, Omega_M = 0.3, and Omega_Lambda = 0.7) have at least one emission line with FWHM larger than 1000 km/s, or have interesting/complex absorption features, are fainter than i=15.0, and have highly reliable redshifts. The area covered by the catalog is 5740 sq. deg. The quasar redshifts range from 0.08 to 5.41, with a median value of 1.48; the catalog includes 891 quasars at redshifts greater than four, of which 36 are at redshifts greater than five. Approximately half of the catalog quasars have i < 19; nearly all have i < 21. For each object the catalog presents positions accurate to better than 0.2 arcsec. rms per coordinate, five-band (ugriz) CCD-based photometry with typical accuracy of 0.03 mag, and information on the morphology and selection method. The catalog also contains basic radio, near-infrared, and X-ray emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra cover the wavelength region 3800--9200A at a spectral resolution of ~2000. The spectra can be retrieved from the public database using the information provided in the catalog. The average SDSS colors of quasars as a function of redshift, derived from the catalog entries, are presented in tabular form. Approximately 96% of the objects in the catalog were discovered by the SDSS.

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arXiv2007

Robust Machine Learning Applied to Astronomical Datasets II: Quantifying Photometric Redshifts for Quasars Using Instance-Based Learning

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. Remaining outliers are simply scattered about the ideal relation, in a similar manner to the pattern seen in the optical for normal galaxies at redshifts z < ~1. The instance-based algorithm is trained on a representative sample of the data and pseudo-blind-tested on the remaining unseen data. The variance between the photometric and spectroscopic redshifts is sigma^2 = 0.123 +/- 0.002 (compared to sigma^2 = 0.265 +/- 0.006 for the CZR), and 54.9 +/- 0.7%, 73.3 +/- 0.6%, and 80.7 +/- 0.3% of the objects are within delta z < 0.1, 0.2, and 0.3 respectively. We also match our sample to the Second Data Release of the Galaxy Evolution Explorer legacy data and the resulting 7,642 objects show a further improvement, giving a variance of sigma^2 = 0.054 +/- 0.005, and 70.8 +/- 1.2%, 85.8 +/- 1.0%, and 90.8 +/- 0.7% of objects within delta z < 0.1, 0.2, and 0.3. We show that the improvement is indeed due to the extra information provided by GALEX, by training on the same dataset using purely SDSS photometry, which has a variance of sigma^2 = 0.090 +/- 0.007. Each set of results represents a realistic standard for application to further datasets for which the spectra are representative.

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arXiv2007

Broad Absorption Line Variability in Repeat Quasar Observations from the Sloan Digital Sky Survey

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 $λ$1549 absorption trough separated from the rest frame of the associated emission peak by more than 3600 km s$^{-1}$. Detached troughs facilitate higher precision variability measurements, since the measurement of the absorption in these objects is not complicated by variation in the emission line flux. We have undertaken a statistical analysis of these detached-trough BALQSO spectra to explore the relationships between BAL features that are seen to vary and the dynamics of emission from the quasar central engine. We have measured variability within our sample, which includes three strongly variable BALs. We have also verified that the statistical behavior of the overall sample agrees with current model predictions and previous studies of BAL variability. Specifically, we observe that the strongest BAL variability occurs among the smallest equivalent width features and at velocities exceeding 12,000 km s$^{-1}$, as predicted by recent disk-wind modeling.

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arXiv2006

Clustering Analyses of 300,000 Photometrically Classified Quasars--I. Luminosity and Redshift Evolution in Quasar Bias

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. We parameterize our clustering amplitudes using realistic dark matter models, and find that a LCDM power spectrum provides a superb fit to our data with a redshift-averaged quasar bias of b_Q = 2.41+/-0.08 ($P_{<χ^2}=0.847$) for $σ_8=0.9$. This represents a better fit than the best-fit power-law model ($ω= 0.0493\pm0.0064θ^ {-0.928\pm0.055}$; $P_{<χ^2}=0.482$). We find b_Q increases with redshift. This evolution is significant at >99.6% using our data set alone, increasing to >99.9999% if stellar contamination is not explicitly parameterized. We measure the quasar classification efficiency across our full sample as a = 95.6 +/- ^{4.4}_{1.9}%, a star-quasar separation comparable with the star-galaxy separation in many photometric studies of galaxy clustering. We derive the mean mass of the dark matter halos hosting quasars as MDMH=(5.2+/-0.6)x10^{12} M_solar/h. At z~1.9 we find a $1.5σ$ deviation from luminosity-independent quasar clustering; this suggests that increasing our sample size by a factor of 1.8 could begin to constrain any luminosity dependence in quasar bias at z~2. Our results agree with recent studies of quasar environments at z < 0.4, which detected little luminosity dependence to quasar clustering on proper scales >50 kpc/h. At z < 1.6, our analysis suggests that b_Q is constant with luminosity to within ~0.6, and that, for g < 21, angular quasar autocorrelation measurements are unlikely to have sufficient statistical power at z < 1.6 to detect any luminosity dependence in quasars' clustering.

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