New Approaches To Photometric Redshift Prediction Via Gaussian Process Regression In The Sloan Digital Sky Survey

Expanding upon the work of Way and Srivastava 2006 we demonstrate how the use of training sets of comparable size continue to make Gaussian process regression (GPR) a competitive approach to that of neural networks and other least-squares fitting methods. This is possible via new large size matrix inversion techniques developed for Gaussian processes (GPs) that do not require that the kernel matrix be sparse. This development, combined with a neural-network kernel function appears to give superior results for this problem. Our best fit results for the Sloan Digital Sky Survey (SDSS) Main Galaxy Sample using u,g,r,i,z filters gives an rms error of 0.0201 while our results for the same filters in the luminous red galaxy sample yield 0.0220. We also demonstrate that there appears to be a minimum number of training-set galaxies needed to obtain the optimal fit when using our GPR rank-reduction methods. We find that morphological information included with many photometric surveys appears, for the most part, to make the photometric redshift evaluation slightly worse rather than better. This would indicate that most morphological information simply adds noise from the GP point of view in the data used herein. In addition, we show that cross-match catalog results involving combinations of the Two Micron All Sky Survey, SDSS, and Galaxy Evolution Explorer have to be evaluated in the context of the resulting cross-match magnitude and redshift distribution. Otherwise one may be misled into overly optimistic conclusions.Comment: 32 pages, ApJ in Press, 2 new figures, 1 new table of comparison methods, updated discussion, references and typos to reflect version in Pres

Photometric redshifts and quasar probabilities from a single, data-driven generative model

We describe a technique for simultaneously classifying and estimating the redshift of quasars. It can separate quasars from stars in arbitrary redshift ranges, estimate full posterior distribution functions for the redshift, and naturally incorporate flux uncertainties, missing data, and multi-wavelength photometry. We build models of quasars in flux-redshift space by applying the extreme deconvolution technique to estimate the underlying density. By integrating this density over redshift one can obtain quasar flux-densities in different redshift ranges. This approach allows for efficient, consistent, and fast classification and photometric redshift estimation. This is achieved by combining the speed obtained by choosing simple analytical forms as the basis of our density model with the flexibility of non-parametric models through the use of many simple components with many parameters. We show that this technique is competitive with the best photometric quasar classification techniques---which are limited to fixed, broad redshift ranges and high signal-to-noise ratio data---and with the best photometric redshift techniques when applied to broadband optical data. We demonstrate that the inclusion of UV and NIR data significantly improves photometric quasar--star separation and essentially resolves all of the redshift degeneracies for quasars inherent to the ugriz filter system, even when included data have a low signal-to-noise ratio. For quasars spectroscopically confirmed by the SDSS 84 and 97 percent of the objects with GALEX UV and UKIDSS NIR data have photometric redshifts within 0.1 and 0.3, respectively, of the spectroscopic redshift; this amounts to about a factor of three improvement over ugriz-only photometric redshifts. Our code to calculate quasar probabilities and redshift probability distributions is publicly available

Astrometric Redshifts for Quasars

The wavelength dependence of atmospheric refraction causes differential chromatic refraction (DCR), whereby objects imaged at different optical/UV wavelengths are observed at slightly different positions in the plane of the detector. Strong spectral features induce changes in the effective wavelengths of broad-band filters that are capable of producing significant positional offsets with respect to standard DCR corrections. We examine such offsets for broad-emission-line (type 1) quasars from the Sloan Digital Sky Survey (SDSS) spanning 0<z<5 and an airmass range of 1.0 to 1.8. These offsets are in good agreement with those predicted by convolving a composite quasar spectrum with the SDSS bandpasses as a function of redshift and airmass. This astrometric information can be used to break degeneracies in photometric redshifts of quasars (or other emission-line sources) and, for extreme cases, may be suitable for determining "astrometric redshifts". On the SDSS's southern equatorial stripe, where it is possible to average many multi-epoch measurements, more than 60% of quasars have emission-line-induced astrometric offsets larger than the SDSS's relative astrometric errors of 25-35 mas. Folding these astrometric offsets into photometric redshift estimates yields an improvement of 9% within Delta z+/-0.1. Future multi-epoch synoptic surveys such as LSST and Pan-STARRS could benefit from intentionally making ~10 observations at relatively high airmass (AM~1.4) in order to improve their photometric redshifts for quasars.Comment: 29 pages, 13 figures (3 color); AJ, accepte

Unusual quasars from the Sloan Digital Sky Survey selected by means of Kohonen self-organising maps

We exploit the spectral archive of the Sloan Digital Sky Survey (SDSS) Data Release 7 to select unusual quasar spectra. The selection method is based on a combination of the power of self-organising maps and the visual inspection of a huge number of spectra. Self-organising maps were applied to nearly 10^5 spectra classified as quasars by the SDSS pipeline. Particular attention was paid to minimise possible contamination by rare peculiar stellar spectral types. We present a catalogue of 1005 quasars with unusual spectra. This large sample provides a useful resource for both studying properties and relations of/between different types of unusual quasars and selecting particularly interesting objects. The spectra are grouped into six types. All these types turn out to be on average more luminous than comparison samples of normal quasars after a statistical correction is made for intrinsic reddening. Both the unusual broad absorption line (BAL) quasars and the strong iron emitters have significantly lower radio luminosities than normal quasars. We also confirm that strong BALs avoid the most radio-luminous quasars. Finally, we create a sample of quasars similar to the two "mysterious" objects discovered by Hall et al. (2002) and briefly discuss the quasar properties and possible explanations of their highly peculiar spectra. (Abstract modified to match the arXiv format)Comment: Added reference to section 6; a few typos corrected; corrections according to the version published in Astronomy and Astrophysic

The Milky Way Tomography with SDSS: III. Stellar Kinematics

We study Milky Way kinematics using a sample of 18.8 million main-sequence stars with r<20 and proper-motion measurements derived from SDSS and POSS astrometry, including ~170,000 stars with radial-velocity measurements from the SDSS spectroscopic survey. Distances to stars are determined using a photometric parallax relation, covering a distance range from ~100 pc to 10 kpc over a quarter of the sky at high Galactic latitudes (|b|>20 degrees). We find that in the region defined by 1 kpc <Z< 5 kpc and 3 kpc <R< 13 kpc, the rotational velocity for disk stars smoothly decreases, and all three components of the velocity dispersion increase, with distance from the Galactic plane. In contrast, the velocity ellipsoid for halo stars is aligned with a spherical coordinate system and appears to be spatially invariant within the probed volume. The velocity distribution of nearby ($Z<1$ kpc) K/M stars is complex, and cannot be described by a standard Schwarzschild ellipsoid. For stars in a distance-limited subsample of stars (<100 pc), we detect a multimodal velocity distribution consistent with that seen by HIPPARCOS. This strong non-Gaussianity significantly affects the measurements of the velocity ellipsoid tilt and vertex deviation when using the Schwarzschild approximation. We develop and test a simple descriptive model for the overall kinematic behavior that captures these features over most of the probed volume, and can be used to search for substructure in kinematic and metallicity space. We use this model to predict further improvements in kinematic mapping of the Galaxy expected from Gaia and LSST.Comment: 90 pages, 26 figures, submitted to Ap

Endbericht zum Projekt ''Fallturm Bremen''

Microgravity research needs earth-bound laboratories as drop towers for efficient use of orbital systems and lowering financial and temporal expenses. On drop towers, the condition of very low residual acceleration (weightlessness) can be attained inside experiment capsules during free fall. The project's objective was to build up a laboratory which is continuously available and cost-effectively operable. Drop Tower 'Bremen' enables 4.74 s experimental time during free fall over 100 m. Experiments are carried out in drop capsules of maximum 300 kg mass; payload mass is 150 kg in maximum. The drop tube of the tower must be evacuated before every drop. The maximum residual acceleration is 10&quot;-&quot;5 to 10&quot;-&quot;4 m/s&quot;2 (10&quot;-&quot;4 to 10&quot;-&quot;5 g) in the frequency range less than 100 Hz. The operation has demonstrated that microgravity research was opened up for new groups of scientists by installation of this new kind of microgravity laboratory. (orig.)SIGLEAvailable from TIB Hannover: F94B1107+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Forschung und Technologie (BMFT), Bonn (Germany); Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA) GmbH, Bonn (Germany)DEGerman