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USM Photometric Redshifts for Astro - wise

USM Photometric Redshifts for Astro - wise. R. Bender, A. Gabasch, M. Neeser, R. Saglia, J. Snigula. Universitätssternwarte München Ludwig-Maximillians-Universität. Introduction. Photometric Redshifts: deducing redshifts from multiple-band optical and near

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USM Photometric Redshifts for Astro - wise

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  1. USM Photometric Redshiftsfor Astro-wise R. Bender, A. Gabasch, M. Neeser, R. Saglia, J. Snigula Universitätssternwarte München Ludwig-Maximillians-Universität Groningen Workshop (M. Neeser)

  2. 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 Groningen Workshop (M. Neeser)

  3. Spectral Energy Distributions (model input) Galaxies Stars 20 SED´s Groningen Workshop (M. Neeser)

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

  5. Assigning a redshift and SED to each source Groningen Workshop (M. Neeser)

  6. Final SED/redshift fit FDF 2893 Groningen Workshop (M. Neeser)

  7. FDF 2367 Groningen Workshop (M. Neeser)

  8. FDF 914 Groningen Workshop (M. Neeser)

  9. Comparison with zspec 200 FDF spectra Groningen Workshop (M. Neeser)

  10. 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 Groningen Workshop (M. Neeser)

  11. FDF 4940 Groningen Workshop (M. Neeser)

  12. FDF 2497 Groningen Workshop (M. Neeser)

  13. 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. Groningen Workshop (M. Neeser)

  14. 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 Groningen Workshop (M. Neeser)

  15. 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). Groningen Workshop (M. Neeser)

  16. 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 Groningen Workshop (M. Neeser)

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