The miniJPAS survey quasar selection

IV. Classification and redshift estimation with SQUEzE

¹ Departament de Física Quàntica i Astrofísica. Institut de Ciències del Cosmos, Universitat de Barcelona (UB-IEEC), Martí i Franquès 1, 08028 Barcelona, Catalonia, Spain
e-mail: iprafols@fqa.ub.edu
² Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Edifici Cn, Campus UAB, 08193 Bellaterra (Barcelona), Spain
³ Institut d’Estudis Espacials de Catalunya (IEEC), Gran Capità, 2-4 Edifici Nexus, 08034 Barcelona, Spain
⁴ Departamento de Física Matemática, Instituto de Física, Universidade de São Paulo, Rua do Matão 1371, CEP 05508-090 São Paulo, Brazil
⁵ Instituto de Astrofísica de Andalucía (CSIC), P.O. Box 3004, 18080 Granada, Spain
⁶ Aix-Marseille Univ., CNRS, CNES, LAM, 38 rue Frédéric Joliot-Curie, 13388 Marseille, France
⁷ Donostia International Physics Center, Paseo Manuel de Lardizabal 4, 20018 Donostia-San Sebastian, Spain
⁸ Ikerbasque, Basque Foundation for Science, Plaza Euskadi 5, 48009 Bilbao, Spain
⁹ Department of Astronomy, University of Illinois at Urbana Champaign, 1002 W Green St, Urbana, IL 61801, USA
¹⁰ Observatório Nacional, Rua General José Cristino 77, São Cristóvão, 20921-400 Rio de Janeiro, Brazil
¹¹ Instituto de Astrofísica de Andalucía (CSIC), Gta. de la Astronomía s/n, 18008 Granada, Spain
¹² Instituto de Física, Universidade Federal da Bahia, Campus Universitário de Ondina - Ondina, Salvador 40210-340, Brasil
¹³ Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Unidad Asociada al CSIC, Plaza San Juan 1, 44001 Teruel, Spain
¹⁴ Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Plaza San Juan 1, 44001 Teruel, Spain
¹⁵ Núcleo de Astrofísica e Cosmologia & Departamento de Física, Universidade Federal do Espírito Santo, Av. Fernando Ferrari 514, 29075-910 Vitória, Brazil
¹⁶ INAF – Osservatorio Astronomico di Trieste, Via Tiepolo 11, 34131 Trieste, Italy
¹⁷ IFPU – Institute for Fundamental Physics of the Universe, Via Beirut 2, 34151 Trieste, Italy
¹⁸ Departamento de Astronomia, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Rua do Matão 1226, Butantã, São Paulo 05508-090, Brasil
¹⁹ Instruments4, 4121 Pembury Place, La Canada Flintridge, CA 91011, USA

Received: 18 July 2023
Accepted: 21 August 2023

Abstract

Aims. Quasar catalogues from photometric data are used in a variety of applications including those targeting spectroscopic follow-up, measurements of supermassive black hole masses, Baryon Acoustic Oscillations, or non-Gaussianities. Here, we present a list of quasar candidates including photometric redshift estimates from the miniJPAS Data Release constructed using SQUEzE. miniJPAS is a small proof-of-concept survey covering 1 deg² with the full J-PAS filter system, consisting of 54 narrow filters and 2 broader filters covering the entire optical wavelength range.

Methods. This work is based on the machine-learning classification of photometric data of quasar candidates using SQUEzE. It has the advantage that its classification procedure can be explained to some extent, making it less of a ‘black box’ when compared with other classifiers. Another key advantage is that the use of user-defined metrics means the user has more control over the classification. While SQUEzE was designed for spectroscopic data, we have adapted it for multi-band photometric data; that is we treat multiple narrow-band filters as very low-resolution spectra. We trained our models using specialised mocks. We estimated our redshift precision using the normalised median absolute deviation, σ_NMAD, applied to our test sample.

Results. Our test sample returns an f₁ score (effectively the purity and completeness) of 0.49 for high-z quasars (with z ≥ 2.1) down a to magnitude of r = 24.3 and 0.24 for low-z quasars (with z < 2.1), also down to a magnitude of r = 24.3. For high-z quasars, this goes up to 0.9 for magnitudes of r < 21.0. We present two catalogues of quasar candidates including redshift estimates: 301 from point-like sources and 1049 when also including extended sources. We discuss the impact of including extended sources in our predictions (they are not included in the mocks), as well as the impact of changing the noise model of the mocks. We also give an explanation of SQUEzE reasoning. Our estimates for the redshift precision using the test sample indicate a σ_NMAD = 0.92% for the entire sample, reduced to 0.81% for r < 22.5 and 0.74% for r < 21.3. Spectroscopic follow-up of the candidates is required in order to confirm the validity of our findings.