J-PAS: Measuring emission lines with artificial neural networks

Abstract

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 zRlarr2 =Rlarr2 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. © ESO 2021. ; G.M.S., R.G.D., R.G.B., E.P., J.R.M., L.A.D.G. and J.M.V. acknowledge support from the State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa" award to the Instituto de Astrofisica de Andalucia (SEV-2017-0709) and the projects AYA2016-77846-P and PID2019-109067-GB100. L.A.D.G. acknowledges support from the Ministry of Science and Technology of Taiwan (grant MOST 106-2628-M-001-003-MY3) and from the Academia Sinica (grant AS-IA-107-M01). P.O.B. acknowledge support from the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior - Brasil (CAPES) -Finance Code 001. R.A.D. acknowledges support from the CNPq through BP grant 308105/2018-4, and FINEP grants REF. 1217/13 -01.13.0279.00 and REF 0859/10 -01.10.0663.00 and also FAPERJ PRONEX grant E-26/110.566/2010 for hardware funding support for the JPAS project through the National Observatory of Brazil and Centro Brasileiro de Pesquisas Fisicas. S.C. thanks CNPq, grant No. 307467/2017-1. V.M. thanks CNPq (Brazil) and FAPES (Brazil) for partial financial support. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 888258. LSJ acknowledges support from Brazilian agencies FAPESP (2019/10923-5) and CNPq (304819/201794). A.C. acknowledges support from PNPD/CAPES. J.M.V. acknowledges financial support from research projects AYA2016-79724-C4-4-P, PID2019-107408GB-C44 from the Spanish Ministerio de Ciencia e Innovacion. The authors acknowledge the following people for providing valuable comments and suggestions on the first draft of this paper: Stravos Akras, Joel Bregman, Salvador Duarte Puertas, Jorge Iglesias, Yolanda Jimenez Teja, Jose Miguel Rodriguez Espinosa, David Sobral and, Adi Zitrin. This research made use of Python (http://www.python.org), Numpy (Van Der Walt et al. 2011); of Matplotlib (Hunter 2007), a suite of open-source Python modules that provides a framework for creating scientific plots and, Astropy, the communitydeveloped core python package (Astropy Collaboration 2013, 2018). Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, and the US Department of Energy Office of Science. The SDSS-III web site is http://www.sdss3.org.This study makes use of the results based on the Calar Alto Legacy Integral Field Area (CALIFA) survey (http://califa.caha.es/).This project made use of the MaNGA-Pipe3D dataproducts. We thank the IA-UNAM MaNGA team for creating this catalogue, and the ConaCyt-180125 project for supporting them. Funding for the J-PAS Project has been provided by the Governments of Espana and Aragon though the Fondo de Inversion de Teruel, European FEDER funding and the MINECO and by the Brazilian agencies FINEP, FAPESP, FAPERJ and by the National Observatory of Brazil. Based on observations made with the JST/T250 telescope and PathFinder camera for the miniJPAS project at the Observatorio Astrofisico de Javalambre (OAJ), in Teruel, owned, managed, and operated by the Centro de Estudios de Fisica del Cosmos de Aragon (CEFCA). We acknowledge the OAJ Data Processing and Archiving Unit (UPAD) for reducing and calibrating the OAJ data used in this work. Funding for OAJ, UPAD, and CEFCA has been provided by the Governments of Spain and Aragon through the Fondo de Inversiones de Teruel; the Aragon Government through the Research Groups E96, E103, and E16_17R; the Spanish Ministry of Science, Innovation and Universities (MCIU/AEI/FEDER, UE) with grant PGC2018-097585-B-C21; the Spanish Ministry of Economy and Competitiveness (MINECO/FEDER, UE) under AYA2015-66211-C2-1-P, AYA2015-66211-C2-2, AYA2012-30789, and ICTS-2009-14; and European FEDER funding (FCDD10-4E-867, FCDD13-4E-2685). ; Peer reviewed