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QSO Catalogue for Gaia GWP-S-335-13000

QSO Catalogue for Gaia GWP-S-335-13000

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QSO Catalogue for Gaia GWP-S-335-13000

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  1. QSO Catalogue for Gaia GWP-S-335-13000 Alexandre H. Andrei (Observatório Nacional/MCT, and associated researcher to Observatório do Valongo/UFRJ and SYRTE/Observatoire de Paris), Anne-Marie Gontier (SYRTE/Observatoire de Paris), Christophe Barache (SYRTE/Observatoire de Paris), Dario N. da Silva Neto (UEZO), François Taris (SYRTE/Observatoire de Paris), Geraldine Bourda (Observatoire de Bordeaux), Jean-François Le Campion (Observatoire de Bordeaux), Jean Souchay (SYRTE/Observatoire de Paris), J.J. Pereira Osório (Observatório Astronômico da Universidade do Porto), Júlio I. Bueno de Camargo (Observatório Nacional/MCT), Marcelo Assafin (Observatório do Valongo/UFRJ), Roberto Vieira Martins (Observatório Nacional/MCT), Sébastien Bouquillon (SYRTE/Observatoire de Paris), Sébastien Lambert (SYRTE/Observatoire de Paris), Sonia Antom (Observatório Astronômico da Universidade do Porto),Patrick Charlot (Observatoire de Bordeaux)‏

  2. CONTENTS 1) CU3QSO astrometric and photometric updates.  100,165 qsos present in at least one available optical image.  compliant to the ICRF to 1.5mas, average zonal errors of 32mas, average precision at 139mas. 2) Photometric redshift.  neural network classifying results  standard astrophysical packages HyperZ and LePHARE 3) Morphology and the signature of the host galaxy.  1343 fields trial on DSS2 and DR7 images leading to 30% PSF excess  all sky DSS mapping on its way 4) Astrometric and photometric variability.  3 years monitoring of 14 long period qsos at the ESO2p2/WFI  relationship between photometric and astrometric variability suggested

  3. 1) CU3QSO astrometric and photometric updates • 100,165 qsos present in at least one available optical image, as recorded in the SDSS DR6, GSC2.3, and USNO B1.0. • average zonal errors of 32mas, • average precision at 139mas. • directly tied and • compliant to the ICRF to 1.5mas

  4. 1) CU3QSO astrometric and photometric updates • The inclusion of the DR7 and the certifying of QSOs off the main optical catalogs add further 41,721 objects. • The DR7 alone brings home 28,224 new objects. • The magnitude and redshift distributions resemble those from the CU3QSO astrometric entries. • But shifted towards dimmer magnitudes, as well as with larger proportion of undetermined magnitudes and redshifts.

  5. 2) Photometric redshift  Neural network classifying results – Aiming to certify the redshift of objects detected only once and/or under not fully reliable conditions. • Trial bench – 53,152 qsos • From the DR7 • BRI colors from the DSS2 • Results: • Standard NN, B,B-R,R-I seeds, 3 neuron levels – σredshift 0.7; Pearson 0.44 • But no agreement if redshift is calculated from fake magnitudes (±2mag at random)‏

  6. 2) Photometric redshift • Results: • 2nd degree complete polynomial on R,B-R,R-I • 3 regimens of solutions z<0.5 0.5<z<1.0 z>1.0 • Further work is needed, and on its way • First results barely at 1σ level of certainty. • SYRTE’s Neural Net, HyperZ, and LePHARE to be explored.

  7. 2) Photometric redshift • Results (at the time of closing this edition): • Another way of evaluating polynomial coefficients is by successive differences • It happens of course to be quite alike to define color loci. • Taking the three colors from B,R,I mags plus a linear combination of magnitudes, one gets σ=0.7z • The adjustments hold well up to z=1.5, enabling to estimate • Further work is needed, and on its way • SYRTE’s Neural Net, HyperZ, and LePHARE to be explored.

  8. 3) Morphology and the signature of the host galaxy • The distinction of QSOs from other AGNs (BLLac, CD, Seyfert) is just a matter of higher degree of brightness, variability, and the presence of the odd spectral line. Or, as the Unified Model goes just a matter of viewing angle. Mullard Space Science Laboratory Astrophysics Group webpage

  9. 3) Morphology and the signature of the host galaxy For AGNs in general, therefore also for QSOs, the host galaxy absolute magnitude should be brighter than -23.5. The host galaxy is thought of most of times be an elliptical or bulge dominated galaxy. The host galaxy luminosity seems to increase proportionally to the strength of the central source, i.e. QSOs host galaxies may expected to usually be brighter than those around less powerful AGNs.  The size of the host galaxy also tends to follow the rule. Typical sizes for BLLac are 13kpc.  Host galaxies have regularly been resolved for AGNs to z < 1.5 and 1arcsec resolution. Less regularly so for QSOs.  The QSO space distribution peaks at • z=0.6 for B=19, and at z=1 for for B=20. • That is, the largest fraction of GAIA QSOs would be of nearby ones. Number of quasars per deg2 as function of redshift and magnitude (Crawford 1994)‏

  10. 3) Morphology and the signature of the host galaxy  One might expect a fair amount of contamination by alien AGNs among the GAIA extragalactic reference frame (because they would look alike by the GAIA QSO selection criteria, and because they still would look a lot pointlike).  One might expect a fair amount of resolved host galaxies around the GAIA extragalactic reference frame QSOs (because the host galaxies do are large and bright enough, because of contamination by alien AGNs, and because the QSOs will be nearby ones). GSC2.3 RORF CFHT

  11. 3) Morphology and the signature of the host galaxy  All sky analysis using DSS2 images. 1arcsec/px, B,V,R plates. 5arcmin2 images centered on each CU3QSO object. Database include the 3 colors (R completed) plus other images when available (e.g. SDSS). • Trial bench on 1,343 R images for which also the SDSS DR7 images (0.396arcsec/px) were retrieved. Extreme magnitudes, colors and redshift stored, along with a representative DR7 sky distribution.  Same IRAF pipeline run on both the DSS2 and DR7 images, to issue 3 PSF parameters: SHARP (probing skewness), SROUND (probing roundness), and GROUND (probing normalness).  Statistics from the in-frame comparison between the QSO and stellar PSF parameters, from the central quartiles average and standard deviation. Only retained frames with 20 or more stellar standards.  Independent treatment for each parameter. Stellar sample defined in two distinct ways, leading to separate results – from all objects above threshold 4σ and from the objects assigned as stellar (class 3) in the DR7.

  12. 3) Morphology and the signature of the host galaxy • The PSF parameters are sound in comparison to the SDSS class separation estimators. • SHARP is the worst behaved parameter, and the only one for which a linear term with magnitude was applied (for the DR7 fields). • The comparison between the extremest cases of QSOs classified as non-stellar testifies both of the better quality of the SDSS images and pixelization, but at the same time of common reckoning on both images. The extreme non-stellar QSOs are 144 in the DSS2 and 86 in the DR7 samples. Of these 50% are common. • The objects not in common should be assigned to the characteristics of ther detectors and measures, as well as possibly to the difference of epochs (cf 3).

  13. 3) Morphology and the signature of the host galaxy • The excess (rate of objects beyond 2σ) of non-stellar quasars is significant as given by all the indicators, on both the DSS2 and DR7 images, measured either against the field stars or the SDSS classified stars. • Effect on the centroid error (assuming a host galaxy two magnitudes fainter than the quasar, and to a brightness distribution following on r2

  14. 4) Astrometric and photometric variability Observations at the ESO Max Planck 2.2m telescope, La Silla, Chile, f8, 0”.238/pixel, WFI 4x2 CCD mosaic, on CCD 7 nearby the optical axis.  Filters Rc/162 (peak 651.7nm, FWHM 162.2nm) and BB#B/123 (peak 451.1nm, FWHM 135.5nm). In each filter 3 frames are taken, to a combined SNR of 1000 (up to 2h total integration time). Variability elements from Teerkopi (2000, A&A 353,77). P ≥ 4y

  15. 4) Astrometric and photometric variability Data Treatment: All images are treated by IRAF MSCRED for trimming, bias, flat, bad-pixel e split. Typically the image treatment enhances the SNR by a factor of 2.  IRAF DAOFIND and PHOT are employed for the determination of centroids and (instrumental) magnitudes, with the entry parameters adjusted for each frame.  Centroids and fluxes are obtained from the adjustment of bi-dimensional gaussians. The inner ring where the object counting is made and the outer ring where the sky background is counted are variable for each object and frame, but their ratio is kept constant.  The plate scale and frame orientation are derived by IRAF IMCOORDS, from UCAC2 catalogue stars.  The following tables bring the measures of precision (pixels). Average precision (1512-0905 sample). Upper row, best imaged objects. Lower row, all detected objects (above threshold 4)‏ Likewise for the R and B filters

  16. 4) Astrometric and photometric variability Data Reduction: (provisional) separated filter solution Object n of frame m Average number of stars appearing at least in two frames [in brackets the minimum and maximum]

  17. 4) Astrometric and photometric variability Results: Time line (415 days) and linear correlations

  18.       “Each player must accept the cards life deals him or her: but once they are in hand, he or she alone must decide how to play the cards in order to win the game.” • Voltaire • (and this WP)‏ • Thank You

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