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Medium-Band Photometric RedshiftsPowerPoint Presentation

Medium-Band Photometric Redshifts

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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

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

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

R=22.9

R=23.8

QSOs: Saturation at R<24rms 0.008

7%-20%outlier

Calibrationoffsetsz biases

Calibrationoffsetsline confusion

QSOs at z~2.8

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?

- 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

ANN

2 template

2 empirical

Collister & Lahav 2004

~0% outliersz/(1+z)>0.1

rmsz/(1+z) = 0.023

Bias ~0.00

~4%outliersz/(1+z)>0.1

rmsz/(1+z) = 0.042

Bias -0.017

~0% outliersz/(1+z)>0.1

rmsz/(1+z) = 0.020

Bias ~0.00

QSOs: Strong Ambiguities

ANN

2 template

2 empirical

Filipe A.

~12% outliersz/(1+z)>0.3

rmsz/(1+z) = 0.113

Bias ~0.00

~22%outliersz/(1+z)>0.3

rmsz/(1+z) = 0.056

Bias +0.015

~1% outliersz/(1+z)>0.3

rmsz/(1+z) ~ 0.04

Bias ~0.000

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