Photometric Redshifts for Cosmological Lensing Lessons from the COSMOS survey

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Photometric Redshifts for Cosmological
LensingLessons from the COSMOS survey

• Peter Capak
• Associate Research Scientist
• IPAC/Caltech

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Overview

• What is COSMOS
• What we learned from COSMOS
• Photo-z (and spec-z) theory
• What work needs to be done

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COSMOS

• 2 sq degree deep multi-wavelength survey
• Designed for Photo-z
• HST imaging
• Ideal for lensing
• Lots of spectroscopy to I26

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COSMOS Lensing Massey et al. 2007, Rhodes et al.
2007, Leauthaud et al. 2007
Contours lensing DM Red x-ray Blue
galaxy mass density
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What we learned from COSMOS
Calibration Matters!

• Need color calibration better than 0.01 mag
• Need template calibration better than 1
• This is the main reason photo-z are considered
  low-accuracy!

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What we learned from COSMOS
High-resolution and photo-z data must be of
similar depth

• Shapes can be measured for much fainter galaxies
  than photo-z are normally used
• Need to carefully design space/ground depths
• have an extrapolation problem

12h in K band
0.62h Hubble F814W
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What we learned from COSMOS
Bright Stars Matter

• Lose 10-20 of area
• Need careful treatment of bright star artifacts

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What we learned from COSMOS
P(zD,Model) ?P(z)

• Photo-z does not give you p(z)
• You get
• p(zD,Model)
• Need prior to break degeneracy
• Prior should be lensing specific!(Massey et al.
  2007)

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Photo-z Theory

• Spec-z measured by identifying spectral features
• Accuracy is dz/(1z)??/?1/R
• Phot-z should be accurate to 0.2
• Clearly more accurate
• So where is the information?

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Photo-z Theory
Redshift

• Information is in the color change as an object
  spectra is red-shifted

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Photo-z Theory

• Photo-z error determined by
• Gradient of color change with redshift
• photometric accuracy

Redshfit
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Photo-z Theory

• Generalized to any filter set
• Ca,b are the color
• Can use a range of template SEDs
• Provides estimate of the phot-z accuracy
• Applies to all methods, not just template fitting

Real Galaxy
Redshfit
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Photo-z Theory

• Works for real galaxies
• Two galaxy types in COSMOS using broad band data
• Estimated (red line) vs actual

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Photo-z Theory

• Degeneracy due to mapping from Color?Redshift
• Need to live with this or get more data

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Photo-z Theory

• Worse results at fainter fluxes
• Need calibration accuracy of 0.01 mag or better!
• More filters not necessarily better

• Best accuracy at filter center
• Gaps in coverage very bad
• Narrow filters improve accuracy
• Overlapping filters improve accuracy

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To Do Photometry

• Better absolute calibration
• Better measurement of system throughput
• Better tracking of atmospheric absorption in IR
• Better photometry techniques
• Better tracking of errors

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To Do Photo-z

• Develop flagging and accurate error estimates
• Account for template uncertainty
• Develop better templates
• Account for variability
• Empirical codes need to work with
  non-representative samples
• could generate templates and priors
• e.g. Budivari et al. 2000, Benitez et al. 2000

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To Do Lensing

• What priors should be used
• What redshift ranges are most important
• Can we live with not using some data?
• Integrate complex probability distributions into
  lensing code

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Conclusions

• Photo-z should be as robust and trustworthy as
  spec-zs
• Main fault is in data quality and lack of
  theoretical understanding
• Recent improvements have come from improved data
  quality
• Now need to focus on improved techniques
• Lensing should integrate inherent uncertainties
  in photo-z into the quantities measured