CROSS-IDENTIFYING DATA RESOURCES IN THE VO ERA
Chilingarian, Igor and Zolotukhin, Ivan
- Software installation/configuration
- General introduction
- Identification of X-ray sources in the Galactic plane (by Ivan Zolotukhin)
- Building FUV-to-NIR SEDs of nearby galaxies (by Igor Chilingarian)
- Discussion and questions
In our tutorial we will provide several examples of cross-matching techniques for data sources available in the Virtual Observatory (VO) using desktop tools and online resources.
Our tutorial contains two independent science cases (Galactic and extragalactic) aimed at demonstrating various techniques for data in different spectral domains with different positional uncertainties. These science cases served as a basis for peer-reviewed publications in major astrophysical journals. We will show the scientifically meaningful usage of the stack of IVOA technologies, and suggest a way to adopt VO infrastructural achievements by a broader community.
Certain parts of this tutorial were successfully held/showcased as separate VO events at Sternberg Astronomical Institute (Russia), Observatoire de Paris and Institut d'Astrophysique de Paris (France), receiving essentially positive feedback among students and purely scientific audience; this experience allowed us to fine-tune the way of presentation for the ADASS audience.
Part #1. Identification of X-ray sources in the Galactic plane. Many objects with hydrogen-rich accretion discs bright in X-ray also exhibit significant H-alpha emission. The input X-ray catalog of Sugizaki et al. (2001) contains about 100 unidentified X-ray objects in the Galactic Plane with positional errors about 1 arcmin. We will explore using TOPCAT some of these sources in the INT Photometric H-Alpha Survey (IPHAS)in order to find any objects with H-alpha emission excess among hundreds of the background stars that fall into the positional uncertainty. For the candidates found we will then try to discover additional X-ray data in the Virtual Observatory which can help to pinpoint the proposed counterparts. This tutorial showcases a VO-based workflow that one can easily set up in the existing VO environment to bring the scientific value for the permanently actual problem of X-ray source identification.
Part #2. Building FUV-to-NIR SEDs of nearby galaxies. We use large online photometric databases, SDSS, UKIDSS, and GALEX to cross-match a list of low- and intermediate-redshift galaxies selected from the SDSS spectral database. We first use Catalog Access Services (CAS), then the STILTS library and a standard HTTP command-line client to access a MultiCone search service. We will discuss several issues complicating the automated SED building of both, technical and astrophysical origin. We will go beyond the ``standard'' catalogue cross-matching and present an automatic VO based generation of image cutouts around the sources of interest falling into the HST footprint using the data from the Hubble Legacy Archive accessed in a batch mode using IVOA Simple Image Access Protocol.
Igor Chilingarian is a postdoctoral researcher at CDS, Observatoire de Strasbourg. His PhD in astrophysics related to evolution of dwarf elliptical galaxies was defended in 2006 at the Moscow State University (Russia) and Universite Claude Bernard Lyon (France). Then he spent 3 years at LERMA, Observatoire de Paris working on galaxy evolution through observations and simulations and developing VO standards. Igor has been involved in both technical and scientific aspects of the VO for 7 years, being an active member of the IVOA Data Models working group since 2005. His most important research result is a discovery of a population of compact elliptical galaxies made with the Virtual Observatory published in Science in 2009. His best known technological achievement is the GalMer database, a VO resource providing access to numerical simulations of interacting galaxies.
Ivan Zolotukhin is a postdoctoral researcher at Observatoire de Paris (France). He has joined the VO initiative during his undergraduate studies in 2005 and has been doing VO-related research since that time. By 2009 his work resulted in a VO-powered PhD thesis defended at the Moscow State University (Russia) which comprised several VO-Science use cases. Being passionate about web applications, during these years Ivan has been taking part in the development of several value-added web services which implemented wide range of IVOA standards. Presently, Ivan pursues his independent VO-Science research, mostly related to X-ray binaries and open cluster subsystem in our Galaxy.
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