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Register a new userExploration of Large Digital Sky Surveys
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S.G. Djorgovski
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We review some of the scientific opportunities and technical challenges posed by the exploration of the large digital sky surveys, in the context of a Virtual Observatory (VO). The VO paradigm will profoundly change the way observational astronomy is done. Clustering analysis techniques can be used to discover samples of rare, unusual, or even previously unknown types of astronomical objects and phenomena. Exploration of the previously poorly probed portions of the observable parameter space are especially promising. We illustrate some of the possible types of studies with examples drawn from DPOSS; much more complex and interesting applications are forthcoming. Development of the new tools needed for an efficient exploration of these vast data sets requires a synergy between astronomy and information sciences, with great potential returns for both fields.
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One of the new frontiers of astronomical research is the exploration of time variability on the sky at different wavelengths and flux levels. We have carried out a pilot project using DPOSS data to study strong variables and transients, and are now extending it to the new Palomar-QUEST synoptic sky survey. We report on our early findings and outline the methodology to be implemented in preparation for a real-time transient detection pipeline. In addition to large numbers of known types of highly variable sources (e.g., SNe, CVs, OVV QSOs, etc.), we expect to find numerous transients whose nature may be established by a rapid follow-up. Whereas we will make all detected variables publicly available through the web, we anticipate that email alerts would be issued in the real time for a subset of events deemed to be the most interesting. This real-time process entails many challenges, in an effort to maintain a high completeness while keeping the contamination low. We will utilize distributed Grid services developed by the GRIST project, and implement a variety of advanced statistical and machine learning techniques.
We present the novel, semi-automated clustering tool ASPECT for analysing voluminous archives of spectra. The heart of the program is a neural network in form of Kohonens self-organizing map. The resulting map is designed as an icon map suitable for the inspection by eye. The visual analysis is supported by the option to blend in individual object properties such as redshift, apparent magnitude, or signal-to-noise ratio. In addition, the package provides several tools for the selection of special spectral types, e.g. local difference maps which reflect the deviations of all spectra from one given input spectrum (real or artificial). ASPECT is able to produce a two-dimensional topological map of a huge number of spectra. The software package enables the user to browse and navigate through a huge data pool and helps him to gain an insight into underlying relationships between the spectra and other physical properties and to get the big picture of the entire data set. We demonstrate the capability of ASPECT by clustering the entire data pool of 0.6 million spectra from the Data Release 4 of the Sloan Digital Sky Survey (SDSS). To illustrate the results regarding quality and completeness we track objects from existing catalogues of quasars and carbon stars, respectively, and connect the SDSS spectra with morphological information from the GalaxyZoo project.
The Baryon Acoustic Oscillation (BAO) feature in the power spectrum of galaxies provides a standard ruler to probe the accelerated expansion of the Universe. The current surveys covering a comoving volume sufficient to unveil the BAO scale are limited to redshift $z lesssim 0.7$. In this paper, we study several galaxy selection schemes aiming at building an emission-line-galaxy (ELG) sample in the redshift range $0.6<z<1.7$, that would be suitable for future BAO studies using the Baryonic Oscillation Spectroscopic Survey (BOSS) spectrograph on the Sloan Digital Sky Survey (SDSS) telescope. We explore two different colour selections using both the SDSS and the Canada France Hawai Telescope Legacy Survey (CFHT-LS) photometry in the u, g, r, and i bands and evaluate their performance selecting luminous ELG. From about 2,000 ELG, we identified a selection scheme that has a 75 percent redshift measurement efficiency. This result confirms the feasibility of massive ELG surveys using the BOSS spectrograph on the SDSS telescope for a BAO detection at redshift $zsim1$, in particular the proposed eBOSS experiment, which plans to use the SDSS telescope to combine the use of the BAO ruler with redshift space distortions using emission line galaxies and quasars in the redshift $0.6<z<2.2$.
(Abridged) Typically large telescope construction and operation costs scale up faster than their collecting area. This slows scientific progress, making it expensive and complicated to increase telescope size. A metric that represents the capability of an imaging survey telescopes, and that captures a wide range of science objectives, is the telescope grasp -- the amount of volume of space in which a standard candle is detectable per unit time. We provide an analytic expression for the grasp, and also show that in the background-dominated noise limit, the optimal exposure time is three times the dead time. We introduce a related metric we call the information-content grasp, which summarizes the variance of all sources observed by the telescope per unit time. For seeing-dominated sky surveys, in terms of grasp, etendue, or collecting-area optimization, recent technological advancements make it more cost effective to construct multiple small telescopes rather than a single large telescope with a similar grasp or etendue. Among these key advancements are the availability of large-format back-side illuminated CMOS detectors with <4 micron pixels, well suited to sample standard seeing conditions given typical focal lengths of small fast telescopes. We also discuss the possible use of multiple small telescopes for spectroscopy. We argue that if all the obstacles to implementing cost-effective wide-field imaging and multi-object spectrographs using multiple small telescopes are removed, then the motivation to build new single large-aperture (>1m) visible-light telescopes which are seeing-dominated, will be weakened. These ideas have led to the concept of the, currently under construction, Large-Array Survey Telescope (LAST).
Many open questions in X-ray astronomy are limited by the relatively small number of objects in uniform optically-identified samples, especially when rare subclasses are considered, or subsets isolated to search for evolution or correlations between wavebands. We describe initial results of a program aimed to ultimately yield 10^4 X-ray source identifications--a sample about an order of magnitude larger than earlier efforts. The technique employs X-ray data from the ROSAT All-Sky Survey (RASS), and optical imaging and spectroscopic followup from the Sloan Digital Sky Survey (SDSS). Optical objects in the SDSS catalogs are automatically cross-correlated with RASS X-ray source positions; then priorities for follow-on SDSS optical spectra of candidate counterparts are automatically assigned using an algorithm based on the known fx/fopt ratios for various classes of X-ray emitters. SDSS parameters for optical morphology, magnitude, colors, plus FIRST radio data, serve as proxies for object class. Initial application of this approach to 1400 deg^2 of sky provides a catalog of 1200 spectroscopically confirmed quasars/AGN that are probable RASS identifications. Most of the IDs are new, and only a few percent of the AGN are likely to be random superpositions. The magnitude and redshift ranges of the counterparts extend over 15<m<21 and 0.03<z<3.6. Although most IDs are quasars and Sy 1s, a variety of other AGN subclasses are also sampled. Substantial numbers of rare AGN are found, including more than 130 narrow-line Seyfert 1s and 45 BL Lac candidates. These results already provide a sizeable set of new IDs, show utility of the sample in multi-waveband studies, and demonstrate the capability of the RASS/SDSS approach to efficiently proceed towards the largest homogeneously selected/observed sample of X-ray emitting AGN. Abridged Abstract
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