Proyecto de Investigación: RTI2018-096188-B-I00
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RTI2018-096188-B-I00
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Spatially Resolved Analysis of Neutral Winds, Stars, and Ionized Gas Kinematics with MEGARA/GTC: New Insights on the Nearby Galaxy UGC 10205
(Institute of Physics, 2020-02-06) Catalán Torrecilla, C.; Castillo Morales, Á; Gil de paz, A.; Gallego, J.; Carrasco, E.; Iglesias Páramo, J.; Cedazo, R.; Chamorro Cazorla, M.; Pascual, S.; García Vargas, M. L.; Cardiel, N.; Gómez Álvarez, P.; Pérez Calpena, A.; Martínez Delgado, I.; Dullo, B. T.; Coelho, P. R. T.; Bruzual, G.; Charlot, S.; Agencia Estatal de Investigación (AEI); Universidad Nacional Autónoma de México (UNAM); 0000-0002-8067-0164; 0000-0003-4964-3245; 0000-0001-6150-2854; 0000-0003-1439-7697; 0000-0003-2726-6370; 0000-0002-9351-6051; 0000-0002-9334-2979; 0000-0002-4140-0110; 0000-0003-1846-4826; 0000-0002-6971-5755; 0000-0003-3458-2275; Coelho, P. R. T. [0000-0003-1846-4826]; Unidad de Excelencia Científica María de Maeztu Centro de Astrobiología del Instituto Nacional de Técnica Aeroespacial y CSIC, MDM-2017-0737
We present a comprehensive analysis of the multiphase structure of the interstellar medium (ISM) and the stellar kinematics in the edge-on nearby galaxy UGC 10205 using integral field spectroscopy (IFS) data taken with MultiEspectrografo en GTC de Alta Resolucion para Astronomia (MEGARA) at the GTC. We explore both the neutral and the ionized gas phases using the interstellar Na I D doublet absorption (LR-V setup, R similar to 6000) and the Ha emission line (HR-R setup, R similar to 18000), respectively. The high-resolution data show the complexity of the Ha emission-line profile revealing the detection of up to three kinematically distinct gaseous components. Despite of this fact, a thin-disk model is able to reproduce the bulk of the ionized gas motions in the central regions of UGC 10205. The use of asymmetric drift corrections is needed to reconciliate the ionized and the stellar velocity rotation curves. We also report the detection of outflowing neutral gas material blueshifted by similar to 87 km s(-1). The main physical properties that describe the observed outflow are a total mass M-out = (4.55 +/- 0.06) x 10(7) M-circle dot and a coldgas mass outflow rate (M)over dot(out) = 0.78 +/- 0.03 M-circle dot yr(-1). This work points out the necessity of exploiting highresolution IFS data to understand the multiphase components of the ISM and the multiple kinematical components in the central regions of nearby galaxies.
Galaxy classification: Deep learning on the OTELO and COSMOS databases
(EDP Sciences, 2020-06-25) De Diego, J. A.; Nadolny, J.; Bongiovanni, Á.; Cepa, J.; Povic, M.; Pérez García, A. M.; Padilla Torres, C. P.; Lara López, M. A.; Cerviño, M.; Pérez Martínez, R.; Alfaro, Emilio J.; Castañeda, H. O.; Fernández Lorenzo, M.; Gallego, J.; González, J. J.; González Serrano, J. I.; Pintos Castro, I.; Sánchez Portal, M.; Cedrés, B.; González Otero, M.; Jones, D. Heath; Bland Hawthorn, J.; Ministerio de Economía y Competitividad (MINECO); Agencia Estatal de Investigación (AEI); De Diego, J. A. https://orcid.org/0000-0001-7040-069X; Centros de Excelencia Severo Ochoa, INSTITUTO DE ASTROFISICA DE ANDALUCIA (IAA), SEV-2017-0709; Unidad de Excelencia Científica María de Maeztu Centro de Astrobiología del Instituto Nacional de Técnica Aeroespacial y CSIC, MDM-2017-0737
Context. The accurate classification of hundreds of thousands of galaxies observed in modern deep surveys is imperative if we want to understand the universe and its evolution.Aims. Here, we report the use of machine learning techniques to classify early- and late-type galaxies in the OTELO and COSMOS databases using optical and infrared photometry and available shape parameters: either the Sersic index or the concentration index.Methods. We used three classification methods for the OTELO database: (1) u-r color separation, (2) linear discriminant analysis using u-r and a shape parameter classification, and (3) a deep neural network using the r magnitude, several colors, and a shape parameter. We analyzed the performance of each method by sample bootstrapping and tested the performance of our neural network architecture using COSMOS data.Results. The accuracy achieved by the deep neural network is greater than that of the other classification methods, and it can also operate with missing data. Our neural network architecture is able to classify both OTELO and COSMOS datasets regardless of small differences in the photometric bands used in each catalog.Conclusions. In this study we show that the use of deep neural networks is a robust method to mine the cataloged data.
A radio-jet driven outflow in the Seyfert 2 galaxy NGC 2110?
(EDP Sciences, 2023-05-10) Peralta de Arriba, L.; Alonso Herrero, A.; García Burillo, S.; García Bernete, I.; Villar Martín, M.; García Lorenzo, B.; Davies, R. I.; Rosario, D.; Hönig, S. F.; Levenson, N. A.; Packham, C.; Ramos Almeida, C.; Pereira Santaella, M.; Audibert, A.; Bellocchi, E.; Hicks, E. K. S.; Labiano, Á.; Ricci, C.; Rigopoulou, D.; European Commission (EC); Gobierno de Canarias; University of Oxford; Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT); Ministerio de Ciencia e Innovación (MICINN); Science and Technology Facilities Council (STFC); Centros de Excelencia Severo Ochoa, CENTRO NACIONAL DE BIOTECNOLOGIA (CNB), SEV-2017-0712
We present a spatially-resolved study of the ionised gas in the central 2 kpc of the Seyfert 2 galaxy NGC 2110 and investigate the role of its moderate luminosity radio jet (kinetic radio power of $P_\mathrm{jet} = 2.3 \times 10^{43}\mathrm{erg\ s^{-1}}$). We use new optical integral-field observations taken with the MEGARA spectrograph at GTC. We fit the emission lines with a maximum of two Gaussian components, except at the AGN position where we used three. Aided by existing stellar kinematics, we use the observed velocity and velocity dispersion of the emission lines to classify the different kinematic components. The disc component is characterised by lines with $\sigma \sim 60-200\ \mathrm{km\ s^{-1}}$. The outflow component has typical values of $\sigma \sim 700\ \mathrm{km\ s^{-1}}$ and is confined to the central 400 pc, which is coincident with linear part of the radio jet detected in NGC 2110. At the AGN position, the [O III]$\lambda$5007 line shows high velocity components reaching at least $1000\ \mathrm{km\ s^{-1}}$. This and the high velocity dispersions indicate the presence of outflowing gas outside the galaxy plane. Spatially-resolved diagnostic diagrams reveal mostly LI(N)ER-like excitation in the outflow and some regions in the disc, which could be due to the presence of shocks. However, there is also Seyfert-like excitation beyond the bending of the radio jet, probably tracing the edge of the ionisation cone that intercepts with the disc of the galaxy. NGC 2110 follows well the observational trends between the outflow properties and the jet radio power found for a few nearby Seyfert galaxies. All these pieces of information suggest that part of observed ionised outflow in NGC 2110 might be driven by the radio jet. However, the radio jet was bent at radial distances of 200 pc (in projection) from the AGN, and beyond there, most of the gas in the galaxy disc is rotating.
