GALEX-SDSS photometric redshifts

Sébastien Heinis, Stéphane Arnouts, Tamás Budavári

sebastien@pha.jhu.edu


NOTE: These photometric redshifts mainly give a statistical information; they should be considered with caution when used on an individual object basis.

The sample
The method
The results

The sample

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We use here MIS fields from IR1.1 (687 fields in total); we refer to this dataset hereafter, unless otherwise stated.

These photometric redshifts have been computed on all MIS GALEX sources with a SDSS counterpart with the following restriction:
distance from the field center lower than 0.5deg (fov_radius < 0.5)



In the following, figures use: unless otherwise stated.

There are 592 fields with SDSS overlap, and 589 with SDSS overlap with sources within 0.5 deg of the center. Here is the list of the 589 fields, giving for each field:

The Method

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Since a fraction (588/687) of the IR1.1 MIS fields do not have FUV observations, in order to be homogeneous, the present photometric redshift estimation uses 6 bands: the NUV GALEX band and the u, g, r, i, and z SDSS bands.
We use here the combination of two different methods:
We refer hereafter to these methods by lephare and polyfit respectively. We present the different steps of the method in the following sections.
  1. Calibration of the redshift-magnitude relation

    The first step consists to calibrate a redshift-apparent magnitude relation based on the GALEX NUV band and the SDSS spectroscopic counterparts. We use the 6 bands (NUV, u, g, r, i, z) and the spectroscopic redshift of SDSS galaxies to fit a 3rd degree polynom: z = f(NUV, u, g, r, i, z).
    The polynom coefficients are hereafter used to derive a photometric redshift. Note that this calibration rely on the SDSS spectroscopic sample (selected with r < 17.5), and that the relation derived is, strictly speaking, only valid in the same volume. We explicitly use it in a larger volume in the following.

  2. Template-fitting with no assumption

    We first compute photometric redshifts using lephare with redshift as a free parameter. The code use galaxy, star, and qso templates.

  3. Template-fitting with polyfit redshift assumption

    We then compute photometric redshift using lephare fixing redshift as the one derived from polyfit. The code only uses galaxy templates.

  4. Template fitting with spectroscopic redshift assumption

    We finally compute photometric redshift using lephare fixing redshift as the spectroscopic one. The code only uses galaxy templates.

The results

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Comparison Spectroscopic-Photometric redshifts
Chi2 classification
Predicted type fractions compared to SDSS TYPE classification
Counts by type
Redshift distributions
More plots