usm photometric redshifts for astro - wise
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
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USM Photometric Redshiftsfor Astro-wise
R. Bender, A. Gabasch, M. Neeser, R. Saglia, J. Snigula
Universitätssternwarte MünchenLudwig-Maximillians-Universität
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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
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Spectral Energy Distributions (model input)Galaxies Stars
20 SED´s
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Method:•Filter curvesconvolved withdetectors
•Observed fluxfor each source
•SEDs:convolved withfiltersstepped in redshift
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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
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Final SED/redshift fitFDF 2893
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FDF 2367
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FDF 914
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Comparison with zspec
200 FDF spectra
0.055(1 )zz
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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
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FDF 4940
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FDF 2497
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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.
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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
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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).
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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