A5088653588- Galaxies: Formation, Evolution, Phenomena
- Advanced Vision and Imaging
- Astronomy and Astrophysical Research
- Gamma-ray bursts and supernovae
- Radio Astronomy Observations and Technology
- Remote Sensing in Agriculture
- Astronomical Observations and Instrumentation
- Astrophysical Phenomena and Observations
- CCD and CMOS Imaging Sensors
- Stellar, planetary, and galactic studies
- Adaptive optics and wavefront sensing
- Computational Physics and Python Applications
- Cosmology and Gravitation Theories
- Multidisciplinary Science and Engineering Research
- Maritime Ports and Logistics
- Transport and Economic Policies
- GNSS positioning and interference
- Geography and Environmental Studies in Latin America
- Data Visualization and Analytics
- Astrophysics and Cosmic Phenomena
Instituto de Astrofísica de Canarias
2021
Universidad de La Laguna
2021
Laboratoire d’Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères
2017-2019
Centre National de la Recherche Scientifique
2017-2019
Université Paris Sciences et Lettres
2017-2019
Universidad de Cantabria
2015-2019
Délégation Paris 7
2017-2019
École Nationale Supérieure des Mines de Paris
2018-2019
Université Paris Cité
2019
Instituto de Física de Cantabria
2015-2019
Abstract We present a morphological catalogue for ∼670 000 galaxies in the Sloan Digital Sky Survey two flavours: T-type, related to Hubble sequence, and Galaxy Zoo 2 (GZ2 hereafter) classification scheme. By combining accurate existing visual catalogues with machine learning, we provide largest most up date. The classifications are obtained Deep Learning algorithms using Convolutional Neural Networks (CNNs). use catalogues, GZ2 Nair & Abraham (2010), training CNNs colour images order...
Large scale imaging surveys will increase the number of galaxy-scale strong lensing candidates by maybe three orders magnitudes beyond known today. Finding these rare objects require picking them out at least tens millions images and deriving scientific results from quantifying efficiency bias any search method. To achieve objectives automated methods must be developed. Because gravitational lenses are reducing false positives particularly important. We present a description an open lens...
We use machine learning to identify in color images of high-redshift galaxies an astrophysical phenomenon predicted by cosmological simulations. This phenomenon, called the blue nugget (BN) phase, is compact star-forming phase central regions many growing that follows earlier gas compaction and followed a quenching phase. train Convolutional Neural Network (CNN) with mock "observed" simulated at three phases evolution: pre-BN, BN post-BN, demonstrate CNN successfully retrieves other...
Numerous ongoing and future large area surveys (e.g. DES, EUCLID, LSST, WFIRST), will increase by several orders of magnitude the volume data that can be exploited for galaxy morphology studies. The full potential these only unlocked with development automated, fast reliable analysis methods. In this paper we present DeepLeGATo, a new method two-dimensional photometric profile modeling, based on convolutional neural networks. Our code is trained validated analytic profiles (HST/CANDELS F160W...
Understanding how bulges grow in galaxies is critical step towards unveiling the link between galaxy morphology and star-formation. To do so, it necessary to decompose large sample of at different epochs into their main components (bulges disks). This particularly challenging, especially high redshifts, where are poorly resolved. work presents a catalog bulge-disk decompositions surface brightness profiles ~17.600 H-band selected CANDELS fields (F160W<23, 0<z<2) 4 7 filters covering spectral...
We present a machine learning framework to simulate realistic galaxies for the Euclid Survey. The proposed method combines control on galaxy shape parameters offered by analytic models with surface brightness distributions learned from real Hubble Space Telescope observations deep generative models. field of $0.4\,\rm{deg}^2$ as it will be seen visible imager VIS and show that structural are recovered similar accuracy pure S\'ersic profiles. Based these simulations, we estimate Wide Survey...
ABSTRACT We study the rest-frame optical mass–size relation of bulges and discs from z ∼ 2 to 0 for a complete sample massive galaxies in CANDELS fields using two-component Sérsic models. Discs star-forming follow similar relations. The is less steep than one quiescent (best-fitting slope 0.7 against 0.4 bulges). find little dependence structural properties with global morphology (disc versus bulge dominated) star formation activity (star-forming quiescent). This result suggests mechanisms...
Abstract Establishing accurate morphological measurements of galaxies in a reasonable amount time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or Wide Field Infrared is challenge. Because its high level abstraction with little human intervention, deep learning appears to be promising approach. Deep rapidly growing discipline that models high-level patterns data complex multilayered networks. In this work we test ability convolutional networks provide...
We obtain a sample of 87 radio-loud QSOs in the redshift range 3.6<z<4.4 by cross-correlating sources FIRST radio survey S{1.4GHz} > 1 mJy with star-like objects having r <20.2 SDSS Data Release 7. Of these QSOs, 80 are spectroscopically classified previous work (mainly SDSS), and form training set for search additional such sources. apply our selection to 2,916 FIRST-DR7 pairs find 15 likely candidates. Seven confirmed as high-redshift quasars, bringing total 87. The candidates were...
We present the results of a multi-wavelength study sample high-redshift Radio Loud (RL) Broad Absorption Line (BAL) quasars. This way we extend to higher redshift previous studies on radio properties, and broadband optical colors these objects. have se- lected 22 RL BAL quasars with 3.6 z 4.8 cross-correlating FIRST survey SDSS. Flux densities between 1.25 9.5 GHz been collected JVLA Effelsberg-100m telescopes for 15 14 non-BAL used as compar- ison sample. determine synchrotron peak...