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Bayesian Photometric Redshifts (BPZ)

Bayesian Photometric Redshifts (BPZ). Narciso Ben ítez 1,2 (2000) Narciso Ben ítez 1,2 et al. (2004) Dan Coe 1,2,3 et al. (2006). Johns Hopkins University 1 Instituto de Astrof ísica de Andalucía 2 JPL/Caltech 3. Science Team. Photo-z Methods.

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Bayesian Photometric Redshifts (BPZ)

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  1. Bayesian Photometric Redshifts (BPZ) Narciso Benítez1,2 (2000) Narciso Benítez1,2 et al. (2004) Dan Coe1,2,3 et al. (2006) Johns Hopkins University1 Instituto de Astrofísica de Andalucía2 JPL/Caltech3 Science Team

  2. Photo-z Methods • Spectral Energy Distribution (SED) Template Fitting • Empirical Training Set (Neural Networks)

  3. BPZ v1.99b Bruzual & Charlot ‘03 Benítez ‘00, ‘04 Kinney ‘96 Coe ‘06 Coleman, Wu, Weedman ‘80 Spectral Energy Distribution (SED) templates Normally interpolate 2 between adjacent templates http://adcam.pha.jhu.edu/~txitxo/ recalibrated with real photometry

  4. SED template fit Flux Wavelength

  5. Bayesian use of priors without prior prior: I = 26 Probability with prior with prior Output: Redshift Benítez00

  6. Poorness of Fit Poorest fits yield most accurate redshifts! Benítez00 Redshift Inaccuracy (photo-z vs. spec-z)

  7. 2mod = 0.03 2 = 0.11 2mod = 0.19 2 = 4.27 Flux Wavelength

  8. PHAT GOODS BPZ results (training set) Important to plot error bars and goodness-of-fit

  9. PHAT GOODS BPZ results (training set) Single-peaked P(z) [ODDS  0.95] no error bars plotted

  10. Most GOODS objects have good photometry ACS ground IRAC

  11. …but some are bad ACS ground IRAC

  12. …some are ugly ACS ground IRAC

  13. Robust photo-z’s require Robust photometry One of the best methods(even if Peter doesn’t like it ;)

  14. PSF-corrected aperture-matched photometry What is the best method?

  15. PHOTEST • Photometry Testing • PSF Degradation vs. Model Fitting • Magnitude Uncertainties • Zeropoint Calibration • Object Detection & Deblending • … • Sounds like a job for a new group • Let’s meet in Greece 2009

  16. UDF NICMOS fluxes too low

  17. Objects w/ spec-z NICMOS flux recalibration

  18. Comprehensive Segmentation Map Forced into SExtractor

  19. Wish List(Goals for PHAT?) • Improve SED library • more galaxy types • broader wavelength coverage • SED uncertainties • derived from population synthesis models?? • Improve Priors • using UDF, surveys

  20. Optimal Filter Choicefor a given amount of observing timeBenítez et al. (2008) A&A submitted • 4 - 5 filters is sub-optimal ! • addition of near-IR helps somewhat • > 8 filters performs much better

  21. Filters tested contiguous overlapping  = const   

  22. Photo-z completeness Best is > 8 overlapping filters Depth to which 80% of objects have ODDS ≥ 0.99

  23. Photo-z accuracy for ODDS ≥ 0.99 objects Best is many non-overlapping (contiguous) filters

  24. ALHAMBRA Survey (Moles08)20 medium-band (310Å wide) filters3500 - 9700Å, supplemented by JHKs lab including CCD, atmosphere, mirror reflectivity

  25. ALHAMBRA Survey1.5’ x 1.5’14-filter color imageto cover4+ sq deg

  26. 8,000 - 10,000 sq deg • z < 0.9 - 1.0 • 4 - 5 years • 6 sq deg camera • new 2-3m telescope to be built in Aragon, Spain

  27. PAU Survey: 40 100Å-wide filters (~4000-8000Å) + SDSS u & z

  28. PAU Survey: z/(1+z) < 0.0015 for z < 0.4, L > L*, I < 23 LRGs

  29. PAU Survey: BAO cosmological constraints

  30. PAU Survey: relative w constraints

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