The leading “eigenspectra” from the PCA results are used to define a linear template basis that is used to model the spectra in the redshift analysis. Redshift and classification templates for galaxy, quasar, and CV star classes are constructed by performing a rest-frame principal-component analysis (PCA) of training samples of known redshift. The fits are applied without regard to the target category of the object (so that if an object targeted as a galaxy turns out to be a star, we can identify it as such, although note the exception mentioned above for galaxy targets in BOSS). The best fit model and redshift is chosen and reported for the object. The essential strategy for redshift fitting is to perform, at each potential redshift, a least-squares fit to each spectrum given the uncertainties, using a fairly general set of models, for galaxies, for stars, for cataclysmic variables, and for quasars. The BOSS code includes new redshift and classification templates for stars, galaxies, and quasars, as described in Bolton et al. Otherwise, the idlspec2d codes used in SDSS-I/II and BOSS are very similar. This change relative to SDSS-I/II is motivated by the lower signal-to-noise ratio of BOSS galaxy spectroscopy, which admits spurious and unphysical quasar classifications of galaxy spectra at an unacceptably high rate. These fits do not include quasar templates in the fitting of the spectra of objects targetted as galaxies. Note that for galaxy targets in the DR9 and later BOSS CMASS and LOWZ samples, redshifts should now be selected using Z_NOQSO, Z_ERR_NOQSO, ZWARNING_NOQSO, and CLASS_NOQSO for redshift measurements, errors, warning flags, and classifications (respectively).
#REDSHIFT SPACE DISTORTIONS OF SDSS GALAXIES SOFTWARE#
The software used is called idlspec2d and is publicly available in our software repository.
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