Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies

Author:

Amaro V1,Cavuoti S123ORCID,Brescia M2ORCID,Vellucci C4,Longo G1,Bilicki M56ORCID,de Jong J T A7,Tortora C7,Radovich M8,Napolitano N R2,Buddelmeijer H5ORCID

Affiliation:

1. Department of Physical Sciences, University of Napoli Federico II, via Cinthia 9, I-80126 Napoli, Italy

2. INAF - Astronomical Observatory of Capodimonte, via Moiariello 16, I-80131 Napoli, Italy

3. INFN section of Naples, via Cinthia 6, I-80126, Napoli, Italy

4. DIETI, University of Naples Federico II, Via Claudio, 21, I-80125 Napoli, Italy

5. Leiden Observatory, Leiden University, PO Box 9513, NL-2300 RA Leiden, the Netherlands

6. National Centre for Nuclear Research, Astrophysics Division, PO Box 447, PL-90-950 Łódź, Poland

7. Kapteyn Astronomical Institute, University of Groningen, PO Box 800, NL-9700 AV Groningen, the Netherlands

8. INAF - Osservatorio Astronomico di Padova, via dell’Osservatorio 5, I-35122 Padova, Italy

Funder

Netherlands Organization for Scientific Research

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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2. Machine learning technique for morphological classification of galaxies from the SDSS. III. The CNN image-based inference of detailed features;Kosmìčna nauka ì tehnologìâ;2022-10-28

3. Photometric redshift estimation of galaxies in the DESI Legacy Imaging Surveys;Monthly Notices of the Royal Astronomical Society;2022-10-25

4. Inferring galaxy dark halo properties from visible matter with machine learning;Monthly Notices of the Royal Astronomical Society;2022-09-03

5. Photometric redshifts from SDSS images with an interpretable deep capsule network;Monthly Notices of the Royal Astronomical Society;2022-07-29

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