Volume 647, March 2021
|Number of page(s)||19|
|Published online||26 March 2021|
J-PAS: Measuring emission lines with artificial neural networks
Instituto de Astrofísica de Andalucía (CSIC), PO Box 3004, 18080 Granada, Spain
2 Departamento de Física, Universidade Federal de Santa Catarina, PO Box 476, 88040-900 Florianópolis, SC, Brazil
3 Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Unidad Asociada al CSIC, Plaza San Juan, 1, 44001 Teruel, Spain
4 Donostia International Physics Center (DIPC), Manuel Lardizabal Ibilbidea, 4, San Sebastián, Spain
5 Ikerbasque, Basque Foundation for Science, 48013 Bilbao, Spain
6 Observatório Nacional, Ministério da Ciencia, Tecnologia, Inovação e Comunicações, Rua General José Cristino, 77, São Cristóvão, 20921-400 Rio de Janeiro, Brazil
7 Instituto de Física, Universidade de São Paulo, Rua do Matão 1371, CEP 05508-090 São Paulo, Brazil
8 Departamento de Física, Universidade Federal do Rio Grande do Norte, 59072-970 Natal, RN, Brazil
9 Núcleo de Astrofísica e Cosmologia (Cosmo-ufes) & Departamento de Física, Universidade Federal do Espírito Santo, 29075-910 Vitória, ES, Brazil
10 Instituto de Física, Universidade Federal da Bahia, 40210-340 Salvador, BA, Brazil
11 Observatório do Valongo, Universidade Federal do Rio de Janeiro, 20080-090 Rio de Janeiro, RJ, Brazil
12 Departamento de Astronomia, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil
13 PPGCosmo & Departamento de Fśica, Universidade Federal do Espírito Santo, 29075-910 Vitória, ES, Brazil
14 Instruments4, 4121 Pembury Place, La Cañada-Flintridge, CA 91011, USA
15 Academia Sinica Institute of Astronomy & Astrophysics (ASIAA), 11F of Astronomy-Mathematics Building, AS/NTU, No. 1, Sect. 4, Roosevelt Road, Taipei 10617, Taiwan
16 Department of Astronomy, University of Michigan, 311West Hall, 1085 South University Ave., Ann Arbor, USA
17 Department of Physics and Astronomy, University of Alabama, Box 870324, Tuscaloosa, AL, USA
18 INAF, Osservatorio Astronomico di Trieste, via Tiepolo 11, 34131 Trieste, Italy
19 IFPU, Institute for Fundamental Physics of the Universe, via Beirut 2, 34151 Trieste, Italy
Accepted: 29 December 2020
In the years to come, the Javalambre-Physics of the Accelerated Universe Astrophysical Survey (J-PAS) will observe 8000 deg2 of the northern sky with 56 photometric bands. J-PAS is ideal for the detection of nebular emission objects. This paper presents a new method based on artificial neural networks (ANNs) that is aimed at measuring and detecting emission lines in galaxies up to z = 0.35. These lines are essential diagnostics for understanding the evolution of galaxies through cosmic time. We trained and tested ANNs with synthetic J-PAS photometry from CALIFA, MaNGA, and SDSS spectra. To this aim, we carried out two tasks. First, we clustered galaxies in two groups according to the values of the equivalent width (EW) of Hα, Hβ, [N II], and [O III] lines measured in the spectra. Then we trained an ANN to assign a group to each galaxy. We were able to classify them with the uncertainties typical of the photometric redshift measurable in J-PAS. Second, we utilized another ANN to determine the values of those EWs. Subsequently, we obtained the [N II]/Hα, [O III]/Hβ, and O 3N 2 ratios, recovering the BPT diagram ([O III]/Hβ versus [N II]/Hα). We studied the performance of the ANN in two training samples: one is only composed of synthetic J-PAS photo-spectra (J-spectra) from MaNGA and CALIFA (CALMa set) and the other one is composed of SDSS galaxies. We were able to fully reproduce the main sequence of star-forming galaxies from the determination of the EWs. With the CALMa training set, we reached a precision of 0.092 and 0.078 dex for the [N II]/Hα and [O III]/Hβ ratios in the SDSS testing sample. Nevertheless, we find an underestimation of those ratios at high values in galaxies hosting an active galactic nuclei. We also show the importance of the dataset used for both training and testing the model. Such ANNs are extremely useful for overcoming the limitations previously expected concerning the detection and measurements of the emission lines in such surveys as J-PAS. Furthermore, we show the capability of the method to measure a EW of 10 Å in Hα, Hβ, [N II] and [O III] lines with a signal-to-noise ratio (S/N) of 5, 1.5, 3.5, and 10, respectively, in the photometry. Finally, we compare the properties of emission lines in galaxies observed with miniJPAS and SDSS. Despite the limitation of such a comparison, we find a remarkable correlation in their EWs.
Key words: Galaxy: evolution / surveys / techniques: photometric / methods: data analysis
© ESO 2021
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