Search

The Galaxy And Mass Assembly (GAMA) survey has obtained spectra of over 230 000 targets using the Anglo-Australian Telescope. To homogenize the redshift measurements and improve the reliability, a fully automatic redshift code was developed (autoz). The measurements were made using a cross-correlation method for both the absorption- and the emission-line spectra. Large deviations in the high-pass-filtered spectra are partially clipped in order to be robust against uncorrected artefacts and to reduce the weight given to single-line matches. A single figure of merit (FOM) was developed that puts all template matches on to a similar confidence scale. The redshift confidence as a function of the FOM was fitted with a tanh function using a maximum likelihood method applied to repeat observations of targets. The method could be adapted to provide robust automatic redshifts for other large galaxy redshift surveys. For the GAMA survey, there was a substantial improvement in the reliability of assigned redshifts and in the lowering of redshift uncertainties with a median velocity uncertainty of 33 km s−1. [ABSTRACT FROM AUTHOR]

A great deal of effort is currently being devoted to understanding, estimating and removing systematic errors in cosmological data. In the particular case of Type Ia supernovae, systematics are starting to dominate the error budget. Here we propose a Bayesian tool for carrying out a systematic search for systematic contamination. This serves as an extension to the standard goodness-of-fit tests and allows not only to cross-check raw or processed data for the presence of systematics but also to pin-point the data that are most likely contaminated. We successfully test our tool with mock catalogues and conclude that the Union2.1 data do not possess a significant amount of systematics. Finally, we show that if one includes in Union2.1 the supernovae that originally failed the quality cuts, our tool signals the presence of systematics at over 3.8σ confidence level. [ABSTRACT FROM AUTHOR]