Improving cross-identification of galaxies using their photometry

¹ UNED, Dpto. de Inteligencia Artificial, ETSI Informática, Juan del Rosal, 16, 28040 Madrid, Spain
e-mail: mmarquez92@alumno.uned.es
² Johns Hopkins University, Baltimore MD 21218, USA

Received: 8 September 2013
Accepted: 13 December 2013

Abstract

The identification of the same astronomical objects in different exposures taken with different instruments is a fundamental but difficult problem, which has long been studied for its statistical and computational complexity. We typically consider the celestial coordinates of detections to decide whether they belong to the same object, but crowded areas often yield degenerate cases when multiple matching configurations have similar likelihoods. We applied Bayesian inference to alleviate the problem by including photometric measurements. The spectral energy distribution of a candidate association is compared with models to test whether the photometric evidence points toward a good match or not. We discuss our preliminary results from simulated data and the COSMOS catalog.