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2 March 2006 STScI1 Mining multi-wavelength data in large area surveys with VO tools Yogesh Wadadekar STScI This work is partly supported by a NVO Research.

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Presentation on theme: "2 March 2006 STScI1 Mining multi-wavelength data in large area surveys with VO tools Yogesh Wadadekar STScI This work is partly supported by a NVO Research."— Presentation transcript:

1 2 March 2006 STScI1 Mining multi-wavelength data in large area surveys with VO tools Yogesh Wadadekar STScI This work is partly supported by a NVO Research Initiative award. Collaborator: Stefano Casertano T HE US N ATIONAL V IRTUAL O BSERVATORY

2 2 March 2006 STScI2 Characterizing the Gigahertz radio sky Recent wide area radio surveys contain hundreds of thousands of sources whose physical nature is poorly understood. eg. The VLA B-array FIRST survey (Becker et al. 1995) covers >8000 sq. degrees of sky to a 5 sigma flux limit of 1 mJy at 1.4 GHz. The source catalog contains > 800000 sources NVO Coverage Maps service Area of sky covered by the VLA FIRST survey in galactic coordinates. The sky coverage was chosen to coincide with the Sloan Digital Sky survey coverage.

3 2 March 2006 STScI3 Optical counterparts of FIRST survey radio sources 30% that are identified optically, of these a majority are starburst systems at z ~ 0.2 and the rest are mostly AGN at z ~ 0.5-1.0 (Ivezic et al. 2002) ~70% of VLA B-array FIRST survey radio sources have no detectable optical counterparts in Sloan Survey imaging. Could the missing sources be: obscured AGN/starbursts? high redshift radio loud QSO's? or resolved components of extended radio sources.

4 2 March 2006 STScI4 Mid IR counterparts of FIRST sources mid-IR observations are less susceptible to dust absorption and immune to the Lyman break dropout phenomenon to very high redshifts. The FIRST survey has ~100 sources per square degree. So, a large area and reasonably deep IR survey is essential to identify a statistically significant sample of radio sources.

5 2 March 2006 STScI5 Spitzer SWIRE Legacy Project Observations obtained in the ELAIS N2 region and the Lockman Hole as part of the Spitzer SWIRE survey (Lonsdale et al. 2003) provide an ideal dataset for our purposes. Reduced imaging data and band-merged catalogs are available for 3.6, 4.5, 5.8 and 8.0 microns (IRAC) and 24 microns (MIPS) channels. The two fields also fall entirely within the FIRST and SDSS footprints. The 3.5/4.5 micron observations reach 5 sigma limits of <10 micro Jansky. The 5.8/8.0 channels reach about 40 micro Jansky.

6 2 March 2006 STScI6 Cross matching procedure Identify all FIRST radio sources that lie in “intersection” area of the three datasets – the master radio sample. Match FIRST radio source to the SDSS using OpenSkyQuery DEMO OpenSkyQuery Match the master sample separately to the SWIRE catalog locally. This matching can also be done by building an Openskyquery skynode. Build a database to store outputs from the FIRST- SWIRE and FIRST-SDSS matches. Obtain ancillary imaging data: cutouts for SWIRE, FIRST and SDSS – NVO SIAP Services available. DEMO Analyse the results!

7 2 March 2006 STScI7 OpenSkyQuery: NVO catalog query service Complex SQL queries supported Most common large catalogs from X-Ray through radio included easy to use SQL query builder available.

8 2 March 2006 STScI8 Script to download cutouts from the SDSS - SIAP service import sys,os, MySQLdb # Establish connection to the server, handle exceptions gracefully try: conn = MySQLdb.connect (host = "localhost", user = ”username" passwd = "", db = "swire") except MySQLdb.Error, e: print "Error %d: %s" % (e.args[0], e.args[1]) sys.exit (1) cursor = conn.cursor() # cursor object for processing queries # firsten2 is a table with your master FIRST sample cursor.execute("SELECT distinct radeg,decdeg FROM firsten2") rows = cursor.fetchall ()

9 2 March 2006 STScI9 Python cutout script for row in rows: # download image from SDSS HTTP GET based service os.system('wget "http://casjobs.sdss.org/ImgCutoutDR4/getjpeg.aspx?ra='+str(ro w[0])+'&dec='+str(row[1])+'&scale=0.2&width=150&height=150& opt=PST"'+' -O '+str(row[0])+'_'+str(row[1])+'.jpg') cursor.close() # Close cursor handle conn.close() # Close connection to server print 'Query over'

10 2 March 2006 STScI10 SDSS image cutouts

11 2 March 2006 STScI11 Limitations: hardware and software Cannot upload multiple user tables limitation on size of user tables 5000 row limit on returned results Parallel implementation for full catalog to catalog matches is being worked upon * No SDSS FITS cutout server Work in progress at JHU

12 2 March 2006 STScI12 Limitations: Data and techniques Different random uncertainties in source positions in different catalogs. systematic offsets in astrometry. Needs to be tested for each catalog. Use the NVO tool WCSFixer. Turns out that FIRST, SDSS positions are very good. SWIRE is slightly off, but version 2 catalogs are much better than the version 1.WCSFixer Source deblending errors in catalogs. NVO HyperAtlas concept is under development.HyperAtlas

13 2 March 2006 STScI13 Galaxy mid-IR continuum Mid IR continuum from galaxies has 3 main sources –Emission from small dust grains in H-II regions. –PAH emission from photodissociative regions. –Strong 3-10 micron continuum from the AGN.

14 2 March 2006 STScI14 MIR color color diagram Lacy et al. (2004)

15 2 March 2006 STScI15 Getting more data: Datascope

16 2 March 2006 STScI16 To try things for yourself…. NVO: www.us-vo.org www.us-vo.org WCSFixer: nvo.noao.edu/wcsfixernvo.noao.edu/wcsfixer Coverage maps: irsa.ipac.caltech.edu/applications/QuickStats/ irsa.ipac.caltech.edu/applications/QuickStats/ Openskyquery: www.openskyquery.netwww.openskyquery.net Datascope: heasarc.nasa.gov/voheasarc.nasa.gov/vo


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