A Bayesian hierarchical model for photometric red shifts

Authors: Hurn, Merrilee¹; Green, Peter J.²; Al-Awadhi, Fahimah³

Source: Journal of the Royal Statistical Society: Series C (Applied Statistics), Volume 57, Number 4, September 2008 , pp. 487-504(18)

Publisher: Wiley-Blackwell

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Abstract:

Summary.

The Sloan digital sky survey is an extremely large astronomical survey that is conducted with the intention of mapping more than a quarter of the sky. Among the data that it is generating are spectroscopic and photometric measurements, both containing information about the red shift of galaxies. The former are precise and easy to interpret but expensive to gather; the latter are far cheaper but correspondingly more difficult to interpret. Recently, Csabai and co-workers have described various calibration techniques aiming to predict red shift from photometric measurements. We investigate what a structured Bayesian approach to the problem can add. In particular, we are interested in providing uncertainty bounds that are associated with the underlying red shifts and the classifications of the galaxies. We find that quite a generic statistical modelling approach, using for the most part standard model ingredients, can compete with much more specific custom-made and highly tuned techniques that are already available in the astronomical literature.

Keywords: Bayesian modelling; Calibration; Hierarchical modelling; Markov chain Monte Carlo methods; Photometric red shifts

Document Type: Research article

DOI: http://dx.doi.org/10.1111/j.1467-9876.2008.00621.x

Affiliations: 1: University of Bath, UK 2: University of Bristol, UK 3: Kuwait University, Kuwait

Publication date: 2008-09-01