Suchergebnisse

Full list of authors: González Delgado, R. M.; Díaz-García, L. A.; de Amorim, A.; Bruzual, G.; Cid Fernandes, R.; Pérez, E.; Bonoli, S.; Cenarro, A. J.; Coelho, P. R. T.; Cortesi, A.; García-Benito, R.; López Fernández, R.; Martínez-Solaeche, G.; Rodríguez-Martín, J. E.; Magris, G.; Mejía-Narvaez, A.; Brito-Silva, D.; Abramo, L. R.; Diego, J. M. ; Dupke, R. A.; Hernán-Caballero, A.; Hernández-Monteagudo, C.; López-Sanjuan, C.; Marín-Franch, A.; Marra, V.; Moles, M.; Montero-Dorta, A.; Queiroz, C.; Sodré, L.; Varela, J.; Vázquez Ramió, H.; Vílchez, J. M.; Baqui, P. O.; Benítez, N.; Cristóbal-Hornillos, D.; Ederoclite, A.; Mendes de Oliveira, C.; Civera, T.; Muniesa, D.; Taylor, K.; Tempel, E.; J-PAS Collaboration. ; The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will soon start imaging thousands of square degrees of the northern sky with its unique set of 56 filters (spectral resolution of R - 60). Before the arrival of the final instrument, we observed 1 deg2 on the AEGIS field with an interim camera with all the J-PAS filters. Taking advantage of these data, dubbed miniJPAS, we aim at proving the scientific potential of the J-PAS to derive the stellar population properties of galaxies via fitting codes for spectral energy distributions (SEDs), with the ultimate goal of performing galaxy evolution studies across cosmic time. One parametric (BaySeAGal) and three non-parametric (MUFFIT, AlStar, and TGASPEX) SED-fitting codes are used to constrain the stellar mass, age, metallicity, extinction, and rest-frame and dust-corrected (u-r) colours of a complete flux-limited sample (rSDSS - 22.5 AB) of miniJPAS galaxies that extends up to z = 1. We generally find consistent results on the galaxy properties derived from the different codes, independently of the galaxy spectral type or redshift; this is remarkable considering that 25% of the J-spectra have signal-to-noise ratios (S/N) -3. For galaxies with S=N - 10, we estimate that the J-PAS photometric system will allow us to derive the stellar population properties of rest-frame (u - r) colour, stellar mass, extinction, and mass-weighted age with a precision of 0:04 - 0:02 mag, 0:07 - 0:03 dex, 0:2 - 0:09 mag, and 0:16 - 0:07 dex, respectively. This precision is equivalent to that obtained with spectroscopic surveys of similar S/N. By using the dust-corrected (u - r) colour mass diagram, a powerful proxy for characterizing galaxy populations, we find: (i) that the fraction of red and blue galaxies evolves with cosmic time, with red galaxies being -38% and -18% of the whole population at z = 0:1 and z = 0:5, respectively, and (ii) consistent results between codes for the average intrinsic (u-r) colour, stellar mass, age, and stellar metallicity of blue and red galaxies and their evolution up to z = 1. At all redshifts, the more massive galaxies belong to the red sequence, and these galaxies are typically older and more metal-rich than their counterparts in the blue cloud. Our results confirm that with J-PAS data we will be able to analyse large samples of galaxies up to z - 1, with galaxy stellar masses above log(M?=M-) - 8:9, 9.5, and 9.9 at z = 0:3, 0.5, and 0.7, respectively. The star formation history of a complete sub-sample of galaxies selected at z - 0:1 with log(M=M-) > 8:3 constrains the cosmic evolution of the star formation rate density up to z - 3, in good agreement with results from cosmological surveys. © ESO 2021. ; Acknowledgements. R.G.D., L.A.D.G., R.G.B., G.M.S., J.R.M., and E.P. acknowledge financial support from the State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa" award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709), and to the AYA2016-77846-P and PID2019-109067-GB100. L.A.D.G. also acknowledges financial support by the Ministry of Science and Technology of Taiwan (grant MOST 106-2628-M-001-003-MY3) and by the Academia Sinica (grant AS-IA-107-M01). G.B. acknowledges financial support from the National Autonomous University of México (UNAM) through grant DGAPA/PAPIIT IG100319 and from CONACyT through grant CB2015-252364. SB acknowledges PGC2018-097585-B-C22, MINECO/FEDER, UE of the Spanish Ministerio de Econo-mia, Industria y Competitividad. L.S.J. acknowledges support from Brazilian agencies FAPESP (2019/10923-5) and CNPq (304819/201794). P.O.B. acknowledges support from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. P.R.T.C. acknowledges financial support from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) process number 2018/05392-8 and Conselho Nacional de Desenvolvi-mento Científico e Tecnológico (CNPq) process number 310041/2018-0. V.M. thanks CNPq (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. E.T. acknowledges support by ETAg grant PRG1006 and by EU through the ERDF CoE grant TK133. Based on observations made with the JST/T250 telescope and PathFinder camera for the miniJPAS project at the Observatorio Astrofísico de Javalambre (OAJ), in Teruel, owned, managed, and operated by the Centro de Estudios de Física del Cosmos de Aragón (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 Aragón through the Fondo de Inver-siones de Teruel; the Aragón 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

Full list of authors: Bonoli, S.; Marín-Franch, A.; Varela, J.; Vázquez Ramió, H.; Abramo, L. R.; Cenarro, A. J.; Dupke, R. A.; Vílchez, J. M.; Cristóbal-Hornillos, D.; González Delgado, R. M.; Hernández-Monteagudo, C.; López-Sanjuan, C.; Muniesa, D. J.; Civera, T.; Ederoclite, A.; Hernán-Caballero, A.; Marra, V.; Baqui, P. O.; Cortesi, A.; Cypriano, E. S.; Daflon, S.; de Amorim, A. L.; Díaz-García, L. A.; Diego, J. M.; Martínez-Solaeche, G.; Pérez, E.; Placco, V. M.; Prada, F.; Queiroz, C.; Alcaniz, J.; Alvarez-Candal, A.; Cepa, J.; Maroto, A. L.; Roig, F.; Siffert, B. B.; Taylor, K.; Benitez, N.; Moles, M.; Sodré, L.; Carneiro, S.; Mendes de Oliveira, C.; Abdalla, E.; Angulo, R. E.; Aparicio Resco, M.; Balaguera-Antolínez, A.; Ballesteros, F. J.; Brito-Silva, D.; Broadhurst, T.; Carrasco, E. R.; Castro, T.; Cid Fernandes, R.; Coelho, P.; de Melo, R. B.; Doubrawa, L.; Fernandez-Soto, A.; Ferrari, F.; Finoguenov, A.; García-Benito, R.; Iglesias-Páramo, J.; Jiménez-Teja, Y.; Kitaura, F. S.; Laur, J.; Lopes, P. A. A.; Lucatelli, G.; Martínez, V. J.; Maturi, M.; Overzier, R. A.; Pigozzo, C.; Quartin, M.; Rodríguez-Martín, J. E.; Salzano, V.; Tamm, A.; Tempel, E.; Umetsu, K.; Valdivielso, L. ; von Marttens, R.; Zitrin, A.; Díaz-Martín, M. C.; López-Alegre, G.; López-Sainz, A.; Yanes-Díaz, A.; Rueda-Teruel, F.; Rueda-Teruel, S.; Abril Ibañez, J.; L Antón Bravo, J.; Bello Ferrer, R.; Bielsa, S.; Casino, J. M.; Castillo, J.; Chueca, S.; Cuesta, L.; Garzarán Calderaro, J.; Iglesias-Marzoa, R.; Íniguez, C.; Lamadrid Gutierrez, J. L.; Lopez-Martinez, F.; Lozano-Pérez, D.; Maícas Sacristán, N.; Molina-Ibáñez, E. L.; Moreno-Signes, A.; Rodríguez Llano, S.; Royo Navarro, M.; Tilve Rua, V.; Andrade, U.; Alfaro, E. J.; Akras, S.; Arnalte-Mur, P.; Ascaso, B.; Barbosa, C. E.; Beltrán Jiménez, J.; Benetti, M.; Bengaly, C. A. P.; Bernui, A.; Blanco-Pillado, J. J.; Borges Fernandes, M.; Bregman, J. N.; Bruzual, G.; Calderone, G.; Carvano, J. M.; Casarini, L.; Chaves-Montero, J.; Chies-Santos, A. L.; Coutinho de Carvalho, G.; Dimauro, P.; Duarte Puertas, S.; Figueruelo, D.; González-Serrano, J. I.; Guerrero, M. A.; Gurung-López, S.; Herranz, D.; Huertas-Company, M.; Irwin, J. A.; Izquierdo-Villalba, D.; Kanaan, A.; Kehrig, C.; Kirkpatrick, C. C.; Lim, J.; Lopes, A. R.; Lopes de Oliveira, R.; Marcos-Caballero, A.; Martínez-Delgado, D.; Martínez-González, E.; Martínez-Somonte, G.; Oliveira, N.; Orsi, A. A.; Penna-Lima, M.; Reis, R. R. R.; Spinoso, D.; Tsujikawa, S.; Vielva, P.; Vitorelli, A. Z.; Xia, J. Q.; Yuan, H. B.; Arroyo-Polonio, A.; Dantas, M. L. L.; Galarza, C. A.; Gonçalves, D. R.; Gonçalves, R. S.; Gonzalez, J. E.; Gonzalez, A. H.; Greisel, N.; Jiménez-Esteban, F.; Landim, R. G.; Lazzaro, D.; Magris, G.; Monteiro-Oliveira, R.; Pereira, C. B.; Rebouças, M. J.; Rodriguez-Espinosa, J. M.; Santos da Costa, S.; Telles, E. ; The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will scan thousands of square degrees of the northern sky with a unique set of 56 filters using the dedicated 2:55m Javalambre Survey Telescope (JST) at the Javalambre Astrophysical Observatory. Prior to the installation of the main camera (4:2 deg2 field-of-view with 1.2 Gpixels), the JST was equipped with the JPAS-Pathfinder, a one CCD camera with a 0:3 deg2 field-of-view and plate scale of 0.23 arcsec pixel?1. To demonstrate the scientific potential of J-PAS, the JPAS-Pathfinder camera was used to perform miniJPAS, a _1 deg2 survey of the AEGIS field (along the Extended Groth Strip). The field was observed with the 56 J-PAS filters, which include 54 narrow band (FWHM _ 145 ) and two broader filters extending to the UV and the near-infrared, complemented by the u; g; r; i SDSS broad band filters. In this miniJPAS survey overview paper, we present the miniJPAS data set (images and catalogs), as we highlight key aspects and applications of these unique spectro-photometric data and describe how to access the public data products. The data parameters reach depths of magAB ' 22?23:5 in the 54 narrow band filters and up to 24 in the broader filters (5_ in a 300 aperture). The miniJPAS primary catalog contains more than 64 000 sources detected in the r band and with matched photometry in all other bands. This catalog is 99% complete at r = 23:6 (r = 22:7) mag for point-like (extended) sources. We show that our photometric redshifts have an accuracy better than 1% for all sources up to r = 22:5, and a precision of _0:3% for a subset consisting of about half of the sample. On this basis, we outline several scientific applications of our data, including the study of spatially-resolved stellar populations of nearby galaxies, the analysis of the large scale structure up to z _ 0:9, and the detection of large numbers of clusters and groups. Sub-percent redshift precision can also be reached for quasars, allowing for the study of the large-scale structure to be pushed to z 2. The miniJPAS survey demonstrates the capability of the J-PAS filter system to accurately characterize a broad variety of sources and paves the way for the upcoming arrival of J-PAS, which will multiply this data by three orders of magnitude. © 2021 EDP Sciences. All rights reserved. ; 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 ICTS2009-14; and European FEDER funding (FCDD10-4E-867, FCDD13-4E-2685). This work has made used of CEFCA's Scientific High Performance Computing system which has been funded by the Governments of Spain and Aragon through the Fondo de Inversiones de Teruel, and the Spanish Ministry of Economy and Competitiveness (MINECO-FEDER, grant AYA2012-30789). Funding for the J-PAS project has been provided also by the Brazilian agencies FINEP, FAPESP, FAPERJ and by the National Observatory of Brazil. Additional funding was also provided by the Tartu Observatory and by the Chinese Consortium from the Academy of Sciences SB acknowledges partial support from the project PGC2018-097585-B-C22. R.A.D. acknowledges support from the Conselho Nacional de Desenvolvimento Cientifico e Tecnologico -CNPq through BP grant 308105/2018-4, and the Financiadora de Estudos e Projetos -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 J-PAS project through the National Observatory of Brazil and Centro Brasileiro de Pesquisas Fisicas. LRA acknowledges financial support from CNPq (306696/2018-5) and FAPESP (2015/17199-0). VMthanks CNPq (Brazil) and FAPES (Brazil) for partial financial support and the H2020 project No 888258. L.A.D.G. and K.U. acknowledge 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). J.M.D. and D.H acknowledge the support of project PGC2018-101814-B-100. MQ thanks CNPq (Brazil) and FAPERJ (Brazil) for financial support. PC acknowledges financial support from FAPESP (2018/05392-8) and CNPq (310041/2018-0). AAC acknowledges support from FAPERJ (E26/203.186/2016), CNPq (304971/2016-2 and 401669/2016-5), and the Universidad de Alicante (contract UATALENTO1802). C.Q. acknowledges support from FAPESP (2015/11442-0 and 2019/067661). V.M.P. is supported by NOIRLab, which is managed by AURA under a cooperative agreement with the NSF. P.B acknowledges support from CAPES -Finance Code 001. IAA researchers acknowledge financial 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). Authors acknowledge support from the Generalitat Valenciana project of excellence Prometeo/2020/085. RGD, GMS, JRM, RGB, EP acknowledge financial support from the project AyA2016-77846-P. TC is supported by the INFN INDARK PD51 and PRIN-MIUR 2015W7KAWC. MAR and ALM acknowledge support from the MINECO project FIS2016-78859P(AEI/FEDER, UE). ET, AT and JL acknowledge the support by ETAg grants IUT40-2 and by EU through the ERDF CoE grant TK133 and MOBTP86. CK, JMV, JIP acknowledge financial support from project AYA2016-79724C4-4P. PAAL thanks the support of CNPq (309398/2018-5). LC thanks CNPq for partial support. Y.J-T acknowledges financial support from the FAPERJ (E26/202.835/2016), and from the Horizon 2020 Marie Sklodowska-Curie grant agreement No 898633. DMD acknowledges financial support from the SFB 881 of the DFG and from the MINECO grant AYA2016-81065-C2-2. FP acknowledges support of the project PGC2018-101931-B-I00. JC acknowledges support of the project E AYA2017-88007-C3-1-P, and co-financed by the FEDER. JIGs acknowledges support of projects of reference AYA2017-88007-C3-3-P, and PGC2018-099705-B-I00 and co-financed by the FEDER. EMG and PV would like to acknowledge financial support from the project ESP2017-83921C2-1-R. GMS acknowleges financial support from a predoctoral contract, ref. PRE2018-085523 (MCIU/AEI/FSE, UE). S.C. is partially supported by CNPq. R.G.L. acknowledges CAPES (process 88881.162206/2017-01) and Alexander von Humboldt Foundation for the financial support. JSA acknowledges support from FAPERJ (E26/203.024/2017), CNP (310790/2014-0 and 400471/2014-0) and FINEP (1217/13 -01.13.0279.00 and Ref. 0859/10 -01.10.0663.00). RvM acknowledges support from CNPq. AFS, PAM, VJM and FJB acknowledge support from project AYA2016-81065-C2-2. PAM acknowledges support from the "Subprograma Atraccio de Talent -Contractes Postdoctorals de la Universitat de Valencia". ESC acknowledges support from CNPq (308539/20184) and FAPESP (2019/19687-2). CMdO acknowledges support from CNPq (grant 312333/2014-5) and FAPESP (grant 2009/54202-8). LSJ acknowledges support from CNPq (grant 304819/2017-4) and FAPESP (grant 2012/008004). JMC acknowledges support from CNPq (grant 310727/2016-2). C.H.-M. and N. Greisel also acknowledge the support of the European Union via the Career Integration Grant CIG-PCIG9-GA-2011-294183. JJBP and AMC would like to acknowledge the support from the grant PGC2018-094626-B-C21 and the Basque Government grant IT-979-16. AMC acknowledges the postdoctoral contract from the University of the Basque Country UPV/EHU "Especializacioon de personal investigador doctor" program. MLLD acknowledges CAPES -Finance Code 001; and CNPq (142294/2018-7). GB acknowledges financial support from the UNAM through grant DGAPA/PAPIIT IG100319, from CONACyT through grant CB2015-252364, and from FAPESP projects 2017/02375-2 and 2018/05392-8. M.J. Reboucas acknowledges the support of FAPERJ under a CNE E-26/202.864/2017 grant, and CNPq. Support by CNPq (305409/2016-6) and FAPERJ (E-26/202.841/2017) is acknowledged by DL. AB acknowledges a CNPq fellowship. C.A.G.acknowledges support from CAPES. EA acknowledges support from FAPESP (2011/18729-1). AC acknowledges support from PNPD/CAPES. ABA and FSK acknowledge the Severo Ochoa program SEV-2015-0548. FSK also thanks the AYA2017-89891-P and the RYC2015-18693 grants. DF acknowledges support from the Atraccion del Talento Cientifico en Salamanca programme and the project PGC2018-096038B-I00. ; Peer reviewed

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