Publications

This section contains the publications database that collects IAC articles published in scientific journals. Please, click on the arrow to see full search filter and sort options: author, journal, year, etc..

It also provides access to IAC Preprints Repository here: https://research.iac.es/preprints/

  • A Multiwavelength Look at the GJ 9827 System: No Evidence of Extended Atmospheres in GJ 9827b and d from HST and CARMENES Data
    GJ 9827 is a bright star hosting a planetary system with three transiting planets. As a multiplanet system with planets that sprawl within the boundaries of the radius gap between terrestrial and gaseous planets, GJ 9827 is an optimal target to study the evolution of the atmospheres of close-in planets with a common evolutionary history and their
    Carleo, Ilaria et al.

    Advertised on:

    3
    2021
    Citations
    24
  • A deep learning approach to test the small-scale galaxy morphology and its relationship with star formation activity in hydrodynamical simulations
    Hydrodynamical simulations of galaxy formation and evolution attempt to fully model the physics that shapes galaxies. The agreement between the morphology of simulated and real galaxies, and the way the morphological types are distributed across galaxy scaling relations are important probes of our knowledge of galaxy formation physics. Here, we
    Zanisi, Lorenzo et al.

    Advertised on:

    3
    2021
    Citations
    87
  • A Deep Learning Approach to photospheric Parameters of CARMENES Target Stars
    We construct an individual convolutional neural network architecture for each of the four stellar parameters effective temperature (Teff), surface gravity (log g), metallicity [M/H], and rotational velocity (v sin i). The networks are trained on synthetic PHOENIX-ACES spectra, showing small training and validation errors. We apply the trained
    Passegger, Vera Maria et al.

    Advertised on:

    3
    2021
    Citations
    1
  • A deep learning approach to photospheric parameters of CARMENES target stars
    In the light of more and more new instrumentation to get a deeper insight into the universe, tons of data are collected. While traditional machine-learning methods have been used in processing stellar spectral data, such large new datasets are better handled with Deep Learning (DL) techniques. In this work, we present a Deep Convolutional Neural
    Passegger, Vera Maria et al.

    Advertised on:

    3
    2021
    Citations
    1
  • REVEALING THE STELLAR POPULATIONS OF THE GALACTIC DISK USING THE ESO-VVV SURVEY
    Nuestra privilegiada localización en la Vía Láctea (VL) nos permite estudiar con gran precisión una galaxia espiral típica desde dentro a través de sus poblaciones estelares. Una parte significativa de estas poblaciones estelares está concentrada en el disco de la VL. El disco se extiende por una amplia región del cielo e incluye el disco interior
    Efsan Sokmen

    Advertised on:

    3
    2021
  • Updated BaSTI Stellar Evolution Models and Isochrones. II. α-enhanced Calculations
    This is the second paper of a series devoted to presenting an updated release of the BaSTI (a Bag of Stellar Tracks and Isochrones) stellar model and isochrone library. Following the publication of the updated solar-scaled library, here we present the library for an α-enhanced heavy element distribution. These new α-enhanced models account for all
    Pietrinferni, Adriano et al.

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    2
    2021
    Citations
    146