Publicaciones

Esta sección ofrece el acceso a la base de datos de Publicaciones que recopila los artículos del IAC publicados en revistas científicas. Por favor, pulsa la flecha del menú para ver todas las opciones de búsqueda y de ordenación de resultados; autor, revista, año, etc..

Además ofrece acceso al  repositorio de preprints del IAC: https://research.iac.es/preprints/l

  • Highly porous nature of a primitive asteroid revealed by thermal imaging
    Carbonaceous (C-type) asteroids 1 are relics of the early Solar System that have preserved primitive materials since their formation approximately 4.6 billion years ago. They are probably analogues of carbonaceous chondrites 2,3 and are essential for understanding planetary formation processes. However, their physical properties remain poorly known
    Okada, Tatsuaki et al.

    Fecha de publicación:

    3
    2020
    Número de citas
    90
  • A NICER look at the state transitions of the black hole candidate MAXI J1535-571 during its reflares
    The black hole candidate and X-ray binary MAXI J1535-571 was discovered in 2017 September. During the decay of its discovery outburst, and before returning to quiescence, the source underwent at least four reflaring events, with peak luminosities of ∼10 35-36 erg s -1 (d/4.1 kpc) 2. To investigate the nature of these flares, we analysed a sample of
    Cúneo, V. A. et al.

    Fecha de publicación:

    6
    2020
    Número de citas
    27
  • A planet within the debris disk around the pre-main-sequence star AU Microscopii
    AU Microscopii (AU Mic) is the second closest pre-main-sequence star, at a distance of 9.79 parsecs and with an age of 22 million years 1. AU Mic possesses a relatively rare 2 and spatially resolved 3 edge-on debris disk extending from about 35 to 210 astronomical units from the star 4, and with clumps exhibiting non-Keplerian motion 5-7. Detection
    Plavchan, Peter et al.

    Fecha de publicación:

    6
    2020
    Número de citas
    174
  • Galaxy classification: deep learning on the OTELO and COSMOS databases
    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
    de Diego, José A. et al.

    Fecha de publicación:

    6
    2020
    Número de citas
    14