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Abstract Reference: 30195
Identifier: O6.3
Presentation: Oral communication
Key Theme: 2 Management of Scientific and Data Analysis Projects 


Optimization of Multi-band Galaxies Cataloguing: Description of the Data Mangement Pipeline

Authors:
Márquez María José, Sarro Baro Luis Manuel, Budavári Tamás 

The analysis of multi-band images of cosmological fields presents several technical difficulties related to the assembly of consecutive knowledge extraction tasks from source identification to photometric measurements, cross-matching and source labelling. We present the design of a new software pipeline to carry out some of these tasks in an automatic way using techniques borrowed from the field of artificial intelligence. We aim to provide the community with three open source software modules to i) label sources in an astronomical image according to the probability that each one is blended or contaminated with surrounding sources; ii) extract photometric measurements of extended objects using active contours; and iii) carry out a probabilistic cross-match of sources from different images and bands, using all astro-photometric information available. All this being integrated in a configurable architecture which allows to make the best usage of the differente features. Aspects related to Big Data, memory management and computational cost are an important part in the evaluation of the feasibility of the solution proposed. Finally we show several examples of the application of this pipeline to both real astronomical images and simulated ones.