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PZ-G2 » History » Version 2

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Huan Lin, 10/14/2012 07:53 PM


PZ-G2, PZ-G3, PZ-G4

  • PZ-G2: (Photo-z – spec-z) bias has been plotted against photo-z in bins of width dz=0.1.
  • PZ-G3: Photo-z sigma and sigma68 vs photo-z has been compared against R-8.
  • PZ-G4: Outlier fractions vs photo-z have been compared against R-23.

Prerequisites

DESDM photo-z module neural network photo-z outputs for VVDS-Deep data obtained under goal PZ-G1

Procedure

Use existing IDL code from [[des-photoz:DC6_Photo-z_Challenge|DC6 Photo-z Challenge]], which will:
  1. Divide sample into photo-z bins of width dz = 0.1
  2. Calculate and plot mean of (photo-z - spec-z) vs. photo-z attachment:sv_test_comp_bias.ps
  3. Calculate and plot sigma = standard deviation of (photo-z - spec-z) vs. photo-z
  4. Calculate and plot sigma68 = 68-percentile (photo-z -spec-z) vs. photo-z
  5. Calculate and plot 2-sigma and 3-sigma outlier fractions, defined relative to sigma, vs. photo-z

Verdict

  1. Check against DES science requirement R-8 that sigma68 < 0.12
  2. Check against DES science requirements R-23 that 2-sigma fraction < 0.1 and 3-sigma fraction < 0.015

Consequences

Results from [[des-photoz:DC6_Photo-z_Challenge|DC6 Photo-z Challenge]] indicate that the above requirements should be met or close to being met. If we see significant differences for the real VVDS-Deep data, we will investigate potential causes, starting with:

  1. Potential systematic trends in DES colors/magnitudes vs. RA,Dec, checked by plotting DES photometry vs. existing VVDS or CFHTLS (truth-table) photometry of the VVDS-Deep field
  2. Potential lack of depth in the DES coadd data for the VVDS-Deep field, checked by comparing the sky background noise, seeing FWHM, and photometric zeropoint in the DES coadd images vs. the respective nominal DES main survey full-depth values