sess 2 vollmer

Information about sess 2 vollmer

Published on June 18, 2007

Author: Techy_Guy

Source: authorstream.com

Content

Determination of radio spectra from catalogues and identification of Gigahertz peaked sources (GPS) from the Virtual Observatory:  Determination of radio spectra from catalogues and identification of Gigahertz peaked sources (GPS) from the Virtual Observatory Bernd Vollmer, S. Derriere, T. Krichbaum, T. Boch, B. Gassmann, E. Davoust, P. Dubois, F. Genova, F. Ochsenbein, W. van Driel CDS, Observatoire de Strasbourg, France MPIfR, Bonn, Germany Observatoire Mid- Pyrenees, Toulouse, France Observatoire de Paris, France The project:  The project Aim: extract radio cross-ids / spectra from a homogeneous set of catalogues Scientific goal: datamining to search for peculiar sources (e.g. GPS sources = young radio loud AGNs not well understood) Results: (i) catalogue of radio spectra (VizieR) = added value data for the VO (ii) follow-up observations: search for new GPS sources (ii) prototype of a VO tool for intelligent data discovery Radio surveys:  Radio surveys Single dish Interferometer Systematic / pointed (finder) surveys Main characteristics: - Sky coverage - Frequency m/cm wavelength range - Angular resolution (beamsize) - Sensitivity Cross-identification of radio sources – the influence of frequency:  Cross-identification of radio sources – the influence of frequency 1.9m 35cm 20cm 6cm (Slee 1977) (Paul et al. 1992) (Burns et al. 1983) (Burns et al. 1983) Increasing frequency Example: Cen A Cross-identification of radio sources- the influence of resolution:  Cross-identification of radio sources- the influence of resolution . Green Bank 20cm 10’ Green Bank 6cm 3.5’ VLA, NVSS 20cm 45’’ VLA, FIRST 20cm 5’’ VLA, 20cm (Burns et al. 1983) at a larger distance: Cross-identification of radio sources:  Cross-identification of radio sources Based on on proximity / resolution / source extent comparison of fluxes at the same frequency radio spectrum (radio SED) physical characteristics (e.g. galaxies, SN remnants, AGNs) Steps for cross-identification:  Steps for cross-identification Search for, preparation of and uniformization of radio catalogues Definition of code standards Proximity search Selection based on fluxes at the same frequency Selection based on radio spectrum Self-consistency of the final catalogue SPECFIND VO tool SPECFIND: some example spectra:  SPECFIND: some example spectra SPECFIND:  SPECFIND 22 radio catalogues included 11 different frequencies 3.5 million sources (half of them are from the NVSS) Results: ~760,000 independent associations ~67,000 independent radio spectra with more than 2 independent points -andgt; more than an order of magnitude more than previous works (e.g. Vigotti et al. 1989, Kulkarni et al. 1990) Cross-ids and spectra available in VizieR at CDS (Vollmer et al., 2005a, 2005b) Scientific follow-up project:  Scientific follow-up project Datamining of the SPECFIND database Search for sources with inverted radio spectrum =andgt; possible Gigahertz peaked sources (GPS: young radio loud AGN’s not well understood) or futur mm-VLBI targets Quasi-simultaneous observations of these sources at three frequencies (4.8 GHz, 10.4 GHz, 32 GHz) with the Effelsberg 100m telescope Comparison of spectra from data at different epochs with data at the same epoch =andgt; source variability =andgt; potential candidates for intraday variable (IDV) sources GPS source observations: preliminary results:  GPS source observations: preliminary results more than 50% of the sources are bona fide GPS sources ~20% of the sources are variable ~20% of the sources have flat spectra up to 9 mm andlt;10% uncertain classification Going further with VO capabilities:  Going further with VO capabilities Preparation and uniformization of radio catalogues very time consuming Aim: include a maximum of available radio catalogues (andgt;100) Within the framework of VOTECH at CDS: development of (i) a tool to search for useful catalogues in the Virtual Observatory (ii) a tool to extract relevant information and to uniformise the catalogue information Towards a new VO tool I. Registry query tool:  I. Registry query tool Finding VO resources based on Unified Content Descriptors (UCDs) matching a query (written in Java; uses XMLDV API to get data from an XML registry) relevant resources UCD examples: Radio flux: PHOT_FLUX_RADIO* Right ascension: POS_EQ_RA Declination: POS_EQ_DEC II. Data extraction tool:  II. Data extraction tool Extraction of homogenized data from a heterogeneous set of catalogues (Java; works on XML tables) Customization of the VO « characterization » data model Output: VOTable or ASCII homogenization interface data characterisation Summary:  Summary A tool to extract radio spectra from a large set of radio catalogues is available (SPECFIND) Results for 22 radio catalogues are published and available in VizieR at CDS (Vollmer et al. 2005a,b) Scientific follow-up projet based on the datamining of the SPECFIND spectra is in progress Within the framework of VOTECH at CDS: development of (i) a tool to search for useful radio catalogues in the Virtual Observatory (ii) a tool to extract relevant information from these catalogues and to uniformise the catalogue information

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