Automated measurement of redshift from mid-infrared low resolution spectroscopy

Abstract

We present a new SED-fitting based routine for redshift determination that is optimised for mid-infrared (MIR) low-resolution spectroscopy. Its flexible template scaling increases the sensitivity to slope changes and small scale features in the spectrum, while a new selection algorithm called Maximum Combined Pseudo-Likelihood (MCPL) provides increased accuracy and a lower number of outliers compared to the standard maximum-likelihood (ML) approach. Unlike ML, MCPL searches for local (instead of absolute) maxima of a 'pseudo-likelihood' (PL) function, and combines results obtained for all the templates in the library to weed out spurious redshift solutions. The capabilities of MCPL are demonstrated by comparing its results to those of regular ML and to the optical spectroscopic redshifts of a sample of 491 Spitzer/IRS spectra from sources at 0 0.02) is 14% for MCPL and 22% for ML. chi^2 values for ML solutions are found to correlate with the SNR of the spectra, but not with redshift accuracy. By contrast, the peak value of the normalised combined PL (gamma) is found to provide a good indication on the reliability of the MCPL solution for individual sources. The accuracy and reliability of the redshifts depends strongly on the MIR SED. Sources with significant polycyclic aromatic hydrocarbon emission obtain much better results compared to sources dominated by AGN continuum. Nevertheless, for a given gamma the frequency of accurate solutions and outliers is largely independent on their SED type. This reliability indicator for MCPL solutions allows to select subsamples with highly reliable redshifts. In particular, a gamma>0.15 threshold retains 79% of the sources with dz/(1+z)<0.005 while reducing the outlier rate to 3.8% (abridged).