USM Photometric Redshifts for Astro - wise

18/11/2003 Groningen Workshop (M. Neeser) 1

USM Photometric Redshiftsfor Astro-wise

R. Bender, A. Gabasch, M. Neeser, R. Saglia, J. Snigula

Universitätssternwarte MünchenLudwig-Maximillians-Universität


Introduction• Photometric Redshifts: deducing redshifts from multiple-band optical and near infrared imaging (poor man´s spectroscopy)

• Scientific drivers: Source identifications and redshifts Luminosity functions Star formation histories Large scale structures Cluster searches

• An obvious scientific product for the database catalogues


Spectral Energy Distributions (model input)Galaxies Stars

20 SED´s


Method:•Filter curvesconvolved withdetectors

•Observed fluxfor each source

•SEDs:convolved withfiltersstepped in redshift


Assigning a redshift and SED to each source

22

221

( , )1( , )0.05 ( ,

The best fitting z and SEDs are obtained by minimizing:

Then, the probability of a source being at a givenredshift is

)

determined *

b :*

y

filtNi i

ifilt i i

T L z

f f z SEDz SED

N f z SED

P P P P

*

lim

12 * *

zM M kkze e e


Final SED/redshift fitFDF 2893


FDF 2367


FDF 914


Comparison with zspec

200 FDF spectra

0.055(1 )zz


Limitations of this method•Requires adequate spectral coverage (ie. at least 4 filters)

•Existence of degeneracies in SEDs at some redshifts

•SED input library inadequate to accurately map the coolest stars

•Id´s and redshifts for AGN‘s must be done separately from galaxies


FDF 4940


FDF 2497


Integration into Astro-Wise Pipeline

Envision two modes of operation:

• automatic redshifts and source identification from cataloguecolours assuming given default settings (filters, SED´s) andwith output: zphot, SED, probability, and errors.

• interactive mode with user defined parameters (SED´s, zrange, Mrange ) with simple plotting facilities and filter convolution routines.


Integration into Astro-Wise PipelineClass Photred

Persistent class PhotredConfig()

persistent SED models “ model errors “ filter convolution “ seeing factors “ filter weight (SED error in given filter / bad filter value)

==> each object assigned: z1, z2, MB

(persistent) z1, z2

P1, P2

1, 2

model1, model2


Integration into Astro-Wise Pipeline

Open crucial issues:

1/ class definitions

2/ reliable, consistent photometric redshifts can only be achieved with photometric and PSF uniformity across filter sets. (ie. PSF homogenization across all filters).


Present Implementation of Photometric Redshift Routine

• fortran routines to compute chi-square minimization and redshift probability function

• super mongo routines to display output, with a large number of user defined parameters

Munics interactive source selection

http://capella.usm.uni-muenchen.de/~drory/munics/interactive/S2F1.html

USM Photometric Redshifts for Astro - wise

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