USM Photometric Redshifts for Astro-wise

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USM Photometric Redshifts for Astro-wise R. Bender, A. Gabasch, M. Neeser, R. Saglia, J. Snigula Universitätssternwarte München Ludwig-Maximillians-Universität 18/11/2003 Groningen Workshop (M. Neeser)

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

Spectral Energy Distributions (model input) Galaxies Stars 20 SED´s 18/11/2003 Groningen Workshop (M. Neeser)

Groningen Workshop (M. Neeser) Method: Filter curves convolved with detectors Observed flux for each source SEDs: convolved with filters stepped in redshift 18/11/2003 Groningen Workshop (M. Neeser)

Assigning a redshift and SED to each source 18/11/2003 Groningen Workshop (M. Neeser)

Groningen Workshop (M. Neeser) Final SED/redshift fit FDF 2893 18/11/2003 Groningen Workshop (M. Neeser)

Groningen Workshop (M. Neeser) FDF 2367 18/11/2003 Groningen Workshop (M. Neeser)

Groningen Workshop (M. Neeser) FDF 914 18/11/2003 Groningen Workshop (M. Neeser)

Groningen Workshop (M. Neeser) Comparison with zspec 200 FDF spectra 18/11/2003 Groningen Workshop (M. Neeser)

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

Groningen Workshop (M. Neeser) FDF 4940 18/11/2003 Groningen Workshop (M. Neeser)

Groningen Workshop (M. Neeser) FDF 2497 18/11/2003 Groningen Workshop (M. Neeser)

Integration into Astro-Wise Pipeline Envision two modes of operation: automatic redshifts and source identification from catalogue colours assuming given default settings (filters, SED´s) and with output: zphot, SED, probability, and errors. interactive mode with user defined parameters (SED´s, zrange, Mrange ) with simple plotting facilities and filter convolution routines. 18/11/2003 Groningen Workshop (M. Neeser)

Integration into Astro-Wise Pipeline Class 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) Dz1, Dz2 P1, P2 C1, C2 model1, model2 18/11/2003 Groningen Workshop (M. Neeser)

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

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