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Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case

  • Massimo Brescia
  • Stefano Cavuoti
  • Valeria Amaro
  • Giuseppe Riccio
  • Giuseppe Angora
  • Civita Vellucci
  • Giuseppe Longo
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 822)

Abstract

Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the recent huge increase in the number of publications making use of this new approach. The usage of machine learning methods, however is still far from trivial and many problems still need to be solved. Using the evaluation of photometric redshifts as a case study, we outline the main problems and some ongoing efforts to solve them.

Keywords

Big data Astroinformatics Photometric redshifts 

Notes

Acknowledgements

MB acknowledges the INAF PRIN-SKA 2017 program 1.05.01.88.04 and the funding from MIUR Premiale 2016: MITIC. MB and GL acknowledge the H2020-MSCA-ITN-2016 SUNDIAL (SUrvey Network for Deep Imaging Analysis and Learning), financed within the Call H2020-EU.1.3.1.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.INAF - Osservatorio Astronomico di CapodimonteNapoliItaly
  2. 2.Università degli Studi Federico II - Dipartimento di Fisica “E. Pancini”NapoliItaly
  3. 3.INFN - Napoli UnitNapoliItaly

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