C3, a command-line catalog cross-match tool for large astrophysical catalogs

RICCIO, GIUSEPPEGIUSEPPERICCIOBRESCIA, MassimoMassimoBRESCIACAVUOTI, STEFANOSTEFANOCAVUOTIMERCURIO, AMATAAMATAMERCURIODI GIORGIO, Anna MariaAnna MariaDI GIORGIOMOLINARI, SergioSergioMOLINARI2020-09-022020-09-0220170004-6280http://hdl.handle.net/20.500.12386/27068Modern Astrophysics is based on multi-wavelength data organized into large and heterogeneous catalogs. Hence, the need for efficient, reliable and scalable catalog cross-matching methods plays a crucial role in the era of the petabyte scale. Furthermore, multi-band data have often very different angular resolution, requiring the highest generality of cross-matching features, mainly in terms of region shape and resolution. In this work we present C 3 (Command-line Catalog Cross-match), a multi-platform application designed to efficiently cross-match massive catalogs. It is based on a multi-core parallel processing paradigm and conceived to be executed as a stand-alone command-line process or integrated within any generic data reduction/analysis pipeline, providing the maximum flexibility to the end-user, in terms of portability, parameter configuration, catalog formats, angular resolution, region shapes, coordinate units and cross-matching types. Using real data, extracted from public surveys, we discuss the cross-matching capabilities and computing time efficiency also through a direct comparison with some publicly available tools, chosen among the most used within the community, and representative of different interface paradigms. We verified that the C 3 tool has excellent capabilities to perform an efficient and reliable cross-matching between large data sets. Although the elliptical cross-match and the parametric handling of angular orientation and offset are known concepts in the astrophysical context, their availability in the presented command-line tool makes C 3 competitive in the context of public astronomical tools.STAMPAenC3, a command-line catalog cross-match tool for large astrophysical catalogsArticle10.1088/1538-3873/129/972/0240052-s2.0-85012033996000391969300001https://iopscience.iop.org/article/10.1088/1538-3873/129/972/024005/meta2017PASP..129b4005RFIS/05 - ASTRONOMIA E ASTROFISICAERC sectors::Physical Sciences and Engineering::PE6 Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems::PE6_11 Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)