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Followup of X-CLASS galaxy clusters with GROND Jethro Ridl, Nicolas - PowerPoint PPT Presentation

Followup of X-CLASS galaxy clusters with GROND Jethro Ridl, Nicolas Clerc - MPE A. Rau, J. Greiner, K. Nandra, M.Salvato - also MPE M. Pierre, T. Sadibekova, L. Faccioli - CEA Saclay F. Pacaud - Bonn X-CLASS/GROND: Project Overview Data


  1. Followup of X-CLASS galaxy clusters with GROND Jethro Ridl, Nicolas Clerc - MPE A. Rau, J. Greiner, K. Nandra, M.Salvato - also MPE M. Pierre, T. Sadibekova, L. Faccioli - CEA Saclay F. Pacaud - Bonn

  2. X-CLASS/GROND: Project Overview Data Cosmology Photo-z GROND X-ray Red sequence Simulations Cosmological parameters Astrometry PSF modeling Reduction Position Beta-model Multiple colours Richness CR, HR Background Extension Photometry Generic algorithm GROND SDSS Calibration Stellar locus Standards Calibration and comparision Galaxy photometry CR HR Photometric Z catalogue [ CR, HR, z ] Uncertainty MCMC

  3. X-CLASS/GROND: Project Overview Data Data Cosmology Photo-z Optical X-rays GROND X-ray Red sequence Simulations Cosmological parameters Astrometry PSF modeling Reduction Position Beta-model Multiple colours Richness CR, HR Background Extension Photometry Generic algorithm GROND SDSS Calibration Stellar locus Standards Calibration and comparision Galaxy photometry CR HR Photometric Z catalogue [ CR, HR, z ] Uncertainty MCMC

  4. X-CLASS/GROND: Project Overview Photo-z Data Cosmology Photo-z GROND X-ray Red sequence Simulations Cosmological parameters Position Astrometry PSF modeling Reduction Position Beta-model Multiple colours Richness CR, HR Background Extension Extension Photometry Generic algorithm GROND SDSS Calibration Stellar locus Standards Calibration and comparision Galaxy photometry CR HR Photometry Photometric Z catalogue [ CR, HR, z ] Uncertainty MCMC

  5. X-CLASS/GROND: Project Overview Cosmology Data Cosmology Photo-z GROND X-ray Red sequence Simulations Cosmological parameters Astrometry PSF modeling Reduction Position Beta-model Multiple colours Richness CR, HR Background Extension Photometry Generic algorithm GROND SDSS Calibration Stellar locus Standards Calibration and comparision Galaxy photometry CR HR Photometric Z catalogue Number of clusters as a function of [ CR, HR, z ] Uncertainty redshift, count rate and hardness ratio MCMC

  6. XMM Cluster Archive Super Survey (X-CLASS) • Serendipitous cluster catalogue for archival XMM pointings • 2774 high galactic latitude observations • ~ 830 galaxy clusters extracted based purely on X-rays • Pointings cut to 10ks and 20ks • Same methodology as XMM- XXL/LSS • Optical veto from DSS (nearby galaxies, etc) + ‘guessed-z’ Clerc et al. 2012b

  7. XMM Cluster Archive Super Survey (X-CLASS) � • Higher signal-to-noise sample extracted for cosmological analysis leaving 347 (264) clusters • EXT_LIKE > 40 • EXT > 5 arcsec � • 0.009 < CR < 0.5 cts/s ([0.5-2]keV) • 0.05 < HR < 2 ([1-2]keV/[0.5-1]keV) • ~ 130 (104) clusters have photometric or spectroscopic redshifts in various catalogues Clerc et al. 2012b

  8. GROND r-band seeing Number of observations • Simultaneous 7-channel ( grizJHK ) imager on the MPG/ESO 2.2m telescope at La Silla • Pixel size and FOV - griz : 0.156” over 4.5 arcmin 
 - JHK : 0.6” over 10 arcmin • Median r-band seeing: 1.11 • Optical confirmation of X-ray identified clusters Seeing (arcsec) • Identification of red-sequence galaxy cluster 5-sigma point source limiting magnitudes members Filter 8min4TD 20min4TD • Rapid determination of photometric redshifts g 23.2 24.1 r 22.9 23.8 • Immediate characterisation of the cluster for i 22.3 23.1 future analyses z 22.3 23.0 • Predefined observing blocks to optimize J 20.5 21.0 efficiency H 19.9 20.4 K 19.1 19.4 • 8(20)min4TD = 460s ( 1475s ) in griz

  9. z=0.31 z=0.13 z=0.55 z=0.75

  10. X-CLASS/GROND: Data reduction � • Standard GROND pipeline at MPE provides flat-fielded co-added images in each channel • Photometric part of GROND pipeline at MPE developed for GRBs. Not ideal for use on clusters. • Pipeline developed using SExtractor , PSFEx , Swarp and Scamp (all from Bertin et al.) • Galaxy photometry extracted in consistent aperture across all bands to give accurate colours (SExtractor: MAG_DETMODEL ) • Fields in SDSS footprint calibrated with common stars • Those not in SDSS are calibrated with using standard fields

  11. X-CLASS/GROND: Photometric redshift

  12. X-CLASS/GROND: Photometric redshift • Cluster members and redshift determination based on red- sequence - z relation • Try to find the most likely z for each X-ray detected cluster based on: 1. Distance in multi-colour space to expected red sequence position " ◆ 2 # Σ ✓ c obs − c model L = 1 2 σ exp − 2 σ gal

  13. X-CLASS/GROND: Photometric redshift • Cluster members and redshift determination based on red- sequence - z relation • Try to find the most likely z for each X-ray detected cluster based on: 1. Distance in multi-colour space to expected red sequence position " ◆ 2 # Σ ✓ c obs − c model L = 1 2 σ exp − 2 σ gal

  14. X-CLASS/GROND: Photometric redshift • Cluster members and redshift determination based on red- sequence - z relation • Try to find the most likely z for each X-ray detected cluster based on: 1. Distance in multi-colour space to expected red sequence position 2. Weighted by position relative to beta-model from X-rays " ◆ 2 # � 1 . 5 Σ ✓ c obs − c model L =  1 B 2 σ exp − r (1 + ext ) 2 2 σ gal

  15. X-CLASS/GROND: Photometric redshift • Cluster members and redshift determination based on red- sequence - z relation • Try to find the most likely z for each X-ray detected cluster based on: 1. Distance in multi-colour space to expected red sequence position 2. Weighted by position relative to beta-model from X-rays 3. Further weighted by number of galaxies " ◆ 2 # � 1 . 5 N gal Σ ✓ c obs − c model L =  1 B 2 σ exp − r (1 + ext ) 2 2 σ gal

  16. X-CLASS/GROND: Photo-z’s - Early results • Code run on 29 known-z clusters that fall in GROND and SDSS footprints • Combination of spectro-z’s • Early results are Photo-z encouraging • There are a few problems that have been identified 1. BCG often flagged out of the catalogue 2. Model for the red sequence needs modification Spectro-z 3. Photometric calibration

  17. In summary • GROND is an efficient instrument for getting photo- z’s: to z=0.8 in ~30 min/cluster σ z = 0 . 02 • Still some challenges outstanding e.g. photometric calibration in non-SDSS fields, el Nino … • Not possible to get a local galaxy background in photo-z calculations • Catalogue coming soon • Next step: Cosmology and high redshift clusters

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