Suchergebnisse

Context. The intermediate-mass pre-main sequence Herbig Ae/Be stars are key to understanding the differences in formation mechanisms between low-and high-mass stars. The study of the general properties of these objects is hampered by the lack of a well-defined, homogeneous sample, and because few and mostly serendipitously discovered sources are known. Aims. Our goal is to identify new Herbig Ae/Be candidates to create a homogeneous and well defined catalogue of these objects. Methods. We have applied machine learning techniques to 4 150 983 sources with data from Gaia DR2, 2MASS, WISE, and IPHAS or VPHAS+. Several observables were chosen to identify new Herbig Ae/Be candidates based on our current knowledge of this class, which is characterised by infrared excesses, photometric variabilities, and Hα emission lines. Classical techniques are not efficient for identifying new Herbig Ae/Be stars mainly because of their similarity with classical Be stars, with which they share many characteristics. By focusing on disentangling these two types of objects, our algorithm has also identified new classical Be stars. Results. We have obtained a large catalogue of 8470 new pre-main sequence candidates and another catalogue of 693 new classical Be candidates with a completeness of 78.8ℓ ±ℓ 1.4% and 85.5ℓ ±ℓ 1.2%, respectively. Of the catalogue of pre-main sequence candidates, at least 1361 sources are potentially new Herbig Ae/Be candidates according to their position in the Hertzsprung-Russell diagram. In this study we present the methodology used, evaluate the quality of the catalogues, and perform an analysis of their flaws and biases. For this assessment, we make use of observables that have not been accounted for by the algorithm and hence are selection-independent, such as coordinates and parallax based distances. The catalogue of new Herbig Ae/Be stars that we present here increases the number of known objects of the class by an order of magnitude. ; With funding from the Spanish government through the "María de Maeztu Unit of Excellence" accreditation (MDM-2017-0737)

Context. A sample of low-mass Hα emission line sources at z ∼ 0.4 was studied in the context of the mass-metallicty relation (MZR) and its possible evolution. We drew our sample from the OSIRIS Tunable Emission Line Object (OTELO) survey, which exploits the red tunable filter of OSIRIS at the Gran Telescopio Canarias to perform a blind narrow-band spectral scan in a selected field of the Extended Groth Strip. We were able to directly measure emission line fluxes and equivalent widths from the analysis of OTELO pseudo-spectra. Aims. This study aims to explore the MZR in the very low-mass regime. Our sample reaches stellar masses (M) as low as 10 M, where 63% of the sample have M < 10 M. We also explore the relation of the star formation rate (SFR) and specific SFR with M and gas-phase oxygen abundances, as well as the M-size relation and the morphological classification. Methods. The M were estimated using synthetic rest-frame colours. Using an χ minimization method, we separated the contribution of [N» II]λ6583 to the Hα emission lines. Using the N2 index, we separated active galactic nuclei from star-forming galaxies (SFGs) and estimated the gas metallicity. We studied the morphology of the sampled galaxies qualitatively (visually) and quantitatively (automatically) using high-resolution data from the Hubble Space Telescope-ACS. The physical size of the galaxies was derived from the morphological analysis using GALAPAGOS2/GALFIT, where we fit a single-Sérsic 2D model to each source. Results. We find no evidence for an MZR evolution from comparing our very low-mass sample with local SFGs from the Sloan Digital Sky Survey. Furthermore, the same is true for M-size and M-SFR relations, as we deduce from comparison with recent literature. Morphologically, our sample is mostly (63%) populated by late-Type galaxies, with 13% of early-Type sources. For the first time, we identify one possible candidate outlier in the MZR at z = 0.4. The stellar-mass, metallicity, colour, morphology, and SFR of this source suggest that it is compatible with a transitional dwarf galaxy. ; With funding from the Spanish government through the "María de Maeztu Unit of Excellence" accreditation (MDM-2017-0737)

Aims. In this paper, we aim to study the main properties and luminosity function (LF) of the [O II]3727 emitters detected in the OTELO survey in order to characterise the star formation processes in low-mass galaxies at z ∼ 1.43 and to constrain the faint-end of the LF. Methods. Here, we describe the selection method and analysis of the emitters obtained from narrow-band scanning techniques. In addition, we present several relevant properties of the emitters and discuss the selection biases and uncertainties in the determination of the LF and the star formation rate density (SFRD). Results. We confirmed a total of 60 sources from a preliminary list of 332 candidates as [O II]3727 emitters. Approximately 93% of the emitters have masses in the range of 108 < M*/M⊙ < 109. All of our emitters are classified as late-type galaxies, with a lower value of (u − v) when compared with the rest of the emitters of the OTELO survey. We find that the cosmic variance strongly affects the normalisation (ϕ*) of the LF and explains the discrepancy of our results when compared with those obtained from surveys of much larger volumes. However, we are able to determine the faint-end slope of the LF, namely, α = −1.42 ± 0.06, by sampling the LF down to ∼1 dex lower than in previous works. We present our calculation of the SFRD of our sample and compare it to the value obtained in previous studies from the literature. © ESO 2021. ; JAdD thanks the Instituto de Astrofísica de Canarias (IAC) for its support through the Programa de Excelencia Severo Ochoa and the Gobierno de Canarias for the Programa de Talento Tricontinental grant. This work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under the grants AYA2013-46724-P, AYA2014-58861-C3-1-P, AYA2014-58861-C3-2-P, AYA2014-58861-C3-3-P, AYA2016-75808-R, AYA2016-75931-C2-1-P, AYA2016-75931-C2-2-P, and MDM-2017-0737 (Unidad de Excelencia María de Maeztu, CAB). This work was supported by the project Evolution of Galaxies, of reference AYA2017-88007-C3-1-P, within the "Programa estatal de fomento de la investigación científica y técnica de excelencia del Plan Estatal de Inves-tigación Científica y Técnica y de Innovación (2013–2016)" of the "Agencia Estatal de Investigación del Ministerio de Ciencia, Innovación y Universidades", and co-financed by the FEDER "Fondo Europeo de Desarrollo Regional". This article is based on observations made with the Gran Telescopio Canarias (GTC) at Roque de los Muchachos Observatory of the Instituto de Astrofísica de Canarias on the island of La Palma. This study makes use of data from AEGIS, a multi-wavelength sky survey conducted with the Chandra, GALEX, Hubble, Keck, CFHT, MMT, Subaru, Palomar, Spitzer, VLA, and other telescopes, and is supported in part by the NSF, NASA, and the STFC. Based on observations obtained with MegaPrime/MegaCam, a joint project of the CFHT and CEA/IRFU, at the Canada–France–Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Science de l'Univers of the Centre National de la Recherche Sci-entifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at Terapix available at the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. Based on observations obtained with WIRCam, a joint project of CFHT, Taiwan, Korea, Canada, France, at the Canada–France–Hawaii Telescope (CFHT), which is operated by the National Research Council (NRC) of Canada, the Institute National des Sciences de l'Univers of the Centre National de la Recherche Scientifique of France, and the University of Hawaii. This work is based in part on data products produced at TERAPIX, the WIRDS (WIRcam Deep Survey) consortium, and the Canadian Astronomy Data Centre. This research was supported by a grant from the Agence Nationale de la Recherche ANR-07-BLAN-0228. ; With funding from the Spanish government through the 'Severo Ochoa Centre of Excellence' accreditation (SEV-2017-0709). ; Peer reviewed

Context. Computational techniques are essential for mining large databases produced in modern surveys with value-Added products. Aims. This paper presents a machine learning procedure to carry out a galaxy morphological classification and photometric redshift estimates simultaneously. Currently, only a spectral energy distribution (SED) fitting has been used to obtain these results all at once. Methods. We used the ancillary data gathered in the OTELO catalog and designed a nonsequential neural network that accepts optical and near-infrared photometry as input. The network transfers the results of the morphological classification task to the redshift fitting process to ensure consistency between both procedures. Results. The results successfully recover the morphological classification and the redshifts of the test sample, reducing catastrophic redshift outliers produced by an SED fitting and avoiding possible discrepancies between independent classification and redshift estimates. Our technique may be adapted to include galaxy images to improve the classification. © ESO 2021. ; This work was supported by the project Evolution of Galaxies, of reference AYA2014-58861-C3-1-P and AYA2017-88007-C3-1-P, within the "Programa estatal de fomento de la investigación científica y técnica de excelencia del Plan Estatal de Investigación Científica y Técnica y de Innovación (2013-2016" of the "Agencia Estatal de Investigación del Ministerio de Ciencia, Innovación y Universidades", and co-financed by the FEDER "Fondo Europeo de Desarrollo Regional". JAD is grateful for the support from the UNAM-DGAPA-PASPA 2019 program, the UNAM-CIC, the Canary Islands CIE: Tricontinental Atlantic Campus 2017, and the kind hospitality of the IAC. MP acknowledges financial supports from the Ethiopian Space Science and Technology Institute (ESSTI) under the Ethiopian Ministry of Innovation and Technology (MoIT), and from the Spanish Ministry of Economy and Competitiveness (MINECO) through projects AYA2013-42227-P and AYA2016-76682C3-1-P, and from the Spanish Ministerio de Ciencia e Innovación – Agencia Estatal de Investigación through projects PID2019-106027GB-C41 and AYA2016-76682C3-1-P. APG, MSP and RPM were supported by the PNAYA project: AYA2017–88007–C3–2–P. JG was supported by the PNAYA project AYA2018–RTI-096188-B-i00. MC & APG are also funded by Spanish State Research Agency grant MDM-2017-0737 (Unidad de Excelencia María de Maeztu CAB). JIGS receives support through the Proyecto Puente 52.JU25.64661 (2018) funded by Sodercan S.A. and the Universidad de Cantabria, and PGC2018–099705–B–100 funded by the Ministerio de Ciencia, Innovación y Universidades. EJA acknowledges funding 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 from grant PGC2018-095049-B-C21. Based on observations made with the Gran Telescopio Canarias (GTC), installed in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias, in the island of La Palma. This work is (partly) based on data obtained with the instrument OSIRIS, built by a Consortium led by the Instituto de Astrofísica de Canarias in collaboration with the Instituto de Astronomía of the Universidad Autónoma de México. OSIRIS was funded by GRANTECAN and the National Plan of Astronomy and Astrophysics of the Spanish Government. ; Peer reviewed