1. CLASH/HST photoz estimation: the challenges & their quality Stephanie Jouvel, Ofer Lahav, Ole Host

2. Presentation overview -CLASH observations and photoz codes and photoz quality definitions -Photoz for cluster galaxies -Photoz for high-z galaxies : Arcs for the strong lensing analysis -Conclusion

3. Data and photoz quality CLASH/HST observations = > 16 filters covering 2000 to 17000 AA => detect up to z~4 gal (Balmer) We currently have 3 template fitting codes : -BPZ -Le Phare -Munich’s code (Seitz et al.) We use these codes to estimate the photoz quality in terms of : -Photoz accuracy : NMAD -Number of catastrophic redshift -Median of the zphot-zspec (zp-zs) distribution

4. How do we assess the photoz quality Robust estimator of the photoz scatter : NMAD Normalised Median Absolute Deviation => 1.48*median[|zp-zs|/1+zs] Fraction of catastrophic   zp-zs>0.1 Median (zp-zs)/(1+zs)

5. Identify the photoz problems The data : – Photometry Calibration which will result in big 0pts corrections => Produce biases in photoz results Photometric errors => Impact the photoz scatter and PDZ – Number of filters => Impact photoz accuracy Photoz codes : – Template representativity and diversity – Priors in redshift/template => More likely to produce catastrophic redshifts and bias

6. Template representativity We use Le Phare with the template optimised for the COSMOS survey The COSMOS template fill the color-color space defined by the CLASH observation which is a first validation of the template representativity

7. The CLASH/HST specz data oct 2011 Specz sample of 271 galaxies covering the first 6 CLASH clusters completed Specz catalogue mainly composed by cluster members 0.1<z<0.65. Need to separate the specz catalogue in 2 samples : foreground structure and cluster members (z<0.65) Arcs z>0.65

8. Photoz for cluster galaxies

9. Le Phare’s photoz results for specz cat ACS only (7 filters) UVIS+ACS (11 filters) ACS+NIR (12 filters) UVIS+ACS+NIR (16 filters) NMAD 4.3 to 5.4%(1+z) Median -0.007 to -0.026

10. Le Phare photoz uncertainty Photoz errors underestimated => We then modify the photometric errors bands to achieve this.

11. Le Phare photoz uncertainty With 0.03 photometric errors added in quadrature at all bands Validation of the photoz uncertainties on the whole mag-redshift range

12. BPZ and Le Phare 0pts 1 0.39684 2 0.41308 3 0.23674 4 0.18033 5 0.06161 6 0.05412 7 -0.03166 8 -0.06276 9 -0.10776 10 -0.07174 11 -0.08302 12 0.00659 13 0.00655 14 0.02828 15 0.02167 16 0.02489 #FILTERS zp_offset err_zp F225W 1.888 0.446 F275W 0.109 0.472 F336W 0.012 0.233 F390W -0.074 0.258 F435W 0.000 0.030 F475W 0.000 0.030 F606W 0.000 0.030 F625W 0.000 0.030 F775W 0.000 0.030 F814W 0.000 0.030 F850LP 0.000 0.030 F105W -0.052 0.040 F110W -0.057 0.060 F125W -0.078 0.074 F140W -0.119 0.138 F160W -0.095 0.108 Problems with UVIS ? Or with templates photoz codes are using ?

13. Steph’s photoz results  z <0.1 filters (chisq2 0.9) NMAD abs(zp-zs) 0.1 ACS 74 objects3.9%(1+z) 64 objects 3.0%(1+z) 23% ACS+IR 105 objects 4.4%(1+z) 78 objects 2.8%(1+z) 25% ACS+UVIS 97 objects 4.0%(1+z) 81 objects 3.1%(1+z) 16% ACS+UVIS+IR 109 objects 3.9%(1+z) 83 objects 2.9%(1+z) 23% # median NMAD n_obj ACS 0.0018 0.0285 144 ACS+IR -0.0075 0.0282 144 ACS+UVIS -0.0077 0.027 133 ACS+UVIS+IR -0.0095 0.0276 136 Txitxo’s results 0.15 0.9 Dan’s photoz results "ACS" -0.01806 0.0403 152 1.6% "ACS_NIR" -0.01239 0.0423 175 5.0% "UVIS_ACS" -0.009524 0.0387 170 3.9% "UVIS_ACS_NIR” -0.01268 0.0379 187 4.2%

14. summary We do not need both UVIS and NIR data to find good photoz for galaxies z<0.65 which is expected since the color gradient produced by the Balmer break is in the optical for these redshift range The UVIS data seem to have a calibration problem since both BPZ and Le Phare find big 0pt in this wavelength range Le Phare derives good uncertainty after an addition factor of 0.03 in the photometric errors Both BPZ and Le Phare have consistent results. We reach an NMAD 2.8 to 4%(1+z), median -0.01 and low catastrophic redshift rate for confident redshift

15. Photoz for high-z galaxies – Arcs for strong-lensing analysis

16. Photoz for arcs : Strong-Lensing Photoz for arcs => High-z galaxies 1<z<6  Balmer break at  8000 AA  Lyman break at  2400 AA Need of UVIS or NIR data to detect a color gradient which will help the photoz estimation What photoz quality is necessary for the strong- lensing analysis ?

17. Redshift and Cosmology Lens Efficiency: For a fixed lens redshift, the efficiency increase with source redshift Weak cosmology dependence Bartelmann & Schneider

18. Photoz for Strong-Lensing O. Host, D. Coe

19. Le Phare photoz for specz catalogue Catastrophic redshift for high-redshift galaxies

20. Le Phare photoz for specz catalogue

21. Catastrophic redshift for high-redshift galaxies Le Phare photoz for specz catalogue

22. Catastrophic redshift for high-redshift galaxies c c We can mistake cluster galaxies for background galaxies Le Phare photoz for specz catalogue

23. Catastrophic redshift for high-redshift galaxies Le Phare photoz for high-z galaxies Photoz uncertainty well estimated using ACS only

24. Catastrophic redshift for high-redshift galaxies Le Phare photoz for high-z galaxies

25. Catastrophic redshift for high-redshift galaxies Le Phare photoz for high-z galaxies Photoz uncertainty not as well estimated than using ACS only => Add information that do not help at the color gradient

26. Catastrophic redshift for high-redshift galaxies => can’t tell from photoz uncertainty Le Phare photoz for high-z galaxies Filt NMAD median %outlier ”A" 0.3663 -0.129 73.17 ”UA" 0.1014 -0.038 65.85 ”AN" 0.0945 -0.038 70.73 ”All” 0.0544 -0.023 48.78 Having all 16 filters improves the statistics and %outliers 41 galaxies at z>0.65

27. Summary For the cluster galaxies, you only need optical data to derive unbiased redshifts. Since most of our specz catalogue are composed by cluster galaxies UVIS/NIR do not make a big difference. For high-z galaxies z>0.65, the full HST filters does make a difference. It allows to reduce the number of catastrophic redshifts, the scatter, and gives less skewed distribution. Need to understand the number of catastrophic redshift for high-z galaxies.

28. Le Phare : photoz errors validation

32. Specz cat 22 A383 8 MACS1149 17 A2261 132 MACS1206 78 RXJ1347 14 MACS2129

33. Le Phare photoz errors uncertainty With 0.03 (ACS) 0.04 (NIR) and 0.05 (UVIS)photometric errors added in quadrature at all bands Validation of the photoz uncertainties on the whole mag-redshift range