Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-19T18:21:43.467Z Has data issue: false hasContentIssue false

C3: A Command-line Catalogue Cross-matching tool for modern astrophysical survey data

Published online by Cambridge University Press:  30 May 2017

Giuseppe Riccio
Affiliation:
INAF - Astronomical Observatory of Capodimonte, via Moiariello 16, I-80131 Napoli, Italy
Massimo Brescia
Affiliation:
INAF - Astronomical Observatory of Capodimonte, via Moiariello 16, I-80131 Napoli, Italy
Stefano Cavuoti
Affiliation:
INAF - Astronomical Observatory of Capodimonte, via Moiariello 16, I-80131 Napoli, Italy
Amata Mercurio
Affiliation:
INAF - Astronomical Observatory of Capodimonte, via Moiariello 16, I-80131 Napoli, Italy
Anna Maria Di Giorgio
Affiliation:
INAF - Istituto di Astrofisica e Planetologia Spaziali, Via Fosso del Cavaliere 100, I-00133 Roma, Italy
Sergio Molinari
Affiliation:
INAF - Istituto di Astrofisica e Planetologia Spaziali, Via Fosso del Cavaliere 100, I-00133 Roma, Italy
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In the current data-driven science era, it is needed that data analysis techniques has to quickly evolve to face with data whose dimensions has increased up to the Petabyte scale. In particular, being modern astrophysics based on multi-wavelength data organized into large catalogues, it is crucial that the astronomical catalog cross-matching methods, strongly dependant from the catalogues size, must ensure efficiency, reliability and scalability. Furthermore, multi-band data are archived and reduced in different ways, so that the resulting catalogues may differ each other in formats, resolution, data structure, etc, thus requiring the highest generality of cross-matching features. We present C3 (Command-line Catalogue Cross-match), a multi-platform application designed to efficiently cross-match massive catalogues from modern surveys. Conceived as a stand-alone command-line process or a module within generic data reduction/analysis pipeline, it provides the maximum flexibility, in terms of portability, configuration, coordinates and cross-matching types, ensuring high performance capabilities by using a multi-core parallel processing paradigm and a sky partitioning algorithm.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2017 

References

Becciani, U., et al. 2015 Advanced Environment for Knowledge Discovery in the VIALACTEA Project, Proceedings of ADASS XXV conference, October 2015, Sidney, Australia, in press. eprint arXiv:1511.08619Google Scholar
Benjamin, R. A., et al. 2003 The Publications of the Astronomical Society of the Pacific, 115 (810), 953964 CrossRefGoogle Scholar
Churchwell, E., et al. 2009 Publications of the Astronomical Society of Pacific, 121 (877), 213230 Google Scholar
Du, P., et al., 2014 Science China Physics, Mechanics and Astronomy, 57 (3), 577583 Google Scholar
Gray, L., 2003 Not. Amer. Math. Soc., 50, 200211 Google Scholar
Lucas, P. W., et al. 2008 Monthly Notices of the Royal Astronomical Society, 391 (1), 136163 Google Scholar
Riccio, G., et al. 2016 accepted for publication in The Publications of the Astronomical Society of the Pacific, eprint arXiv:1611.04431Google Scholar
Sciacca, E., et al. 2016 Milky Way analysis through a Science Gateway: Workflows and Resource Monitoring, Proceedings of 8 th International Workshop on Science Gateways, June 2016, Rome, Italy, submitted.Google Scholar
Taylor, M. B., 2006 in Astronomical Data Analysis Software and Systems XV, ed. Gabriel, C., Arviset, C., Ponz, D., & Enrique, S., Astronomical Society of the Pacific Conference Series, 351, 666.Google Scholar
Van Der Walt, S., et al. 2011 Computing in Science and Engineering, 13, 22 Google Scholar