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arXiv · 0812.3568

Optimal filter systems for photometric redshift estimation

Abstract

In the next years, several cosmological surveys will rely on imaging data to estimate the redshift of galaxies, using traditional filter systems with 4-5 optical broad bands; narrower filters improve the spectral resolution, but strongly reduce the total system throughput. We explore how photometric redshift performance depends on the number of filters n_f, characterizing the survey depth through the fraction of galaxies with unambiguous redshift estimates. For a combination of total exposure time and telescope imaging area of 270 hrs m^2, 4-5 filter systems perform significantly worse, both in completeness depth and precision, than systems with n_f >= 8 filters. Our results suggest that for low n_f, the color-redshift degeneracies overwhelm the improvements in photometric depth, and that even at higher n_f, the effective photometric redshift depth decreases much more slowly with filter width than naively expected from the reduction in S/N. Adding near-IR observations improves the performance of low n_f systems, but still the system which maximizes the photometric redshift completeness is formed by 9 filters with logarithmically increasing bandwidth (constant resolution) and half-band overlap, reaching ~0.7 mag deeper, with 10% better redshift precision, than 4-5 filter systems. A system with 20 constant-width, non-overlapping filters reaches only ~0.1 mag shallower than 4-5 filter systems, but has a precision almost 3 times better, dz = 0.014(1+z) vs. dz = 0.042(1+z). We briefly discuss a practical implementation of such a photometric system: the ALHAMBRA survey.

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BibTeXRIS

N. Benitez, M. Moles, J. A. L. Aguerri, E. Alfaro, T. Broadhurst, J. Cabrera, F. J. Castander, J. Cepa, M. Cervino, D. Cristobal-Hornillos, A. Fernandez-Soto, R. M. Gonzalez-Delgado, L. Infante, I. Marquez, V. J. Martinez, J. Masegosa, A. Del Olmo, J. Perea, F. Prada, J. M. Quintana, S. F. Sanchez. 2008-12-18. Optimal filter systems for photometric redshift estimation. https://doi.org/10.1088/0004-637x%2F692%2F1%2Fl5

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