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Medium-Band Photometric Redshifts. UCL Meeting 16 Sep 2008. Christian Wolf. flux / qef. 1000 nm. 400 nm. Redshift Errors & Resolution. Objects at different redshifts Filterset  \'s fixed. z = 0.843. G2 star vs. QSO z=3. z = 1.958. z = 2.828. E. colour. z=0.52. z=0.56. Sb.

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medium band photometric redshifts

Medium-Band Photometric Redshifts

UCL Meeting

16 Sep 2008

Christian Wolf

redshift errors resolution

flux / qef

1000 nm

400 nm

Redshift Errors & Resolution
  • Objects at different redshifts
  • Filterset \'s fixed

z = 0.843

G2 star vs.QSO z=3

z = 1.958

z = 2.828

z bias calibration offsets

E

colour

z=0.52

z=0.56

Sb

colour

Z-Bias & Calibration Offsets
  • N = number of filters, i.e. independent data points
  • Calibration offsets in N=3-D:
    • 1-D normalisation
    • 1-D z-bias
    • 1-D restframe SED bias
    • 1 out of N offset dimensions causes a photo-z bias z
  • More filters  smaller z (proj. component ~1/√N)
  • Narrow filters  small z (larger col/z on feature)
  • Spectroscopy with N~102..3: z without flux calibration
  • Few-filter photo-z’s limited by calibration accuracy
  • Many-filter photo-z’s limited by number and resolution of filters
redshift error regimes

E

colour

z=0.52

z=0.56

Sb

colour

Redshift Error Regimes
  • Three regimes in photo-z quality
  • Saturation
    • Model-data calibration offsets in  test causes p(z)-biases
  • Transition
    • Locally linear colour(z) grid
  • Breakdown
    • Globally nonlinear colour(z) grid

mag

galaxies saturation transition
Galaxies: Saturation & Transition

R=20

R=22

R=23.7

Galaxies at z~0.45

qsos saturation at r 24

R=21.5

R=22.9

R=23.8

QSOs: Saturation at R<24

rms 0.008

7%-20%outlier

Calibrationoffsetsz biases

Calibrationoffsetsline confusion

QSOs at z~2.8

2 sed classification combo 17
2-SED Classification, COMBO-17

Classification ~98% complete at R<23

Stars (~3,000)

White Dwarfs (~30)

Ultra-cool WD (1)

Galaxies (~30,000)

QSOs (~300)

new subject empirical 2 estimation
New Subject:Empirical 2 estimation?
  • 2
    • PDF  Ambiguity warning
  • NN
    • No PDF, no warning
  • Template model
    • Can be extrapolated in z,mag
    • Calibration issues
    • Priors’ issues
  • Empirical model
    • Good priors
    • No calibration issues
    • Can not be extrapolated

Code 2 NN

Model

Template 

Empirical 

galaxies no ambiguities
Galaxies: No Ambiguities

ANN

2 template

2 empirical

Collister & Lahav 2004

~0% outliersz/(1+z)>0.1

rmsz/(1+z) = 0.023

Bias ~0.00

~4%outliersz/(1+z)>0.1

rmsz/(1+z) = 0.042

Bias -0.017

~0% outliersz/(1+z)>0.1

rmsz/(1+z) = 0.020

Bias ~0.00

qsos strong ambiguities
QSOs: Strong Ambiguities

ANN

2 template

2 empirical

Filipe A.

~12% outliersz/(1+z)>0.3

rmsz/(1+z) = 0.113

Bias ~0.00

~22%outliersz/(1+z)>0.3

rmsz/(1+z) = 0.056

Bias +0.015

~1% outliersz/(1+z)>0.3

rmsz/(1+z) ~ 0.04

Bias ~0.000

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