Astrophysical: Methods

  • Publication
    The Milky Way Tomography with SDSS. II. Stellar Metallicity
    Using effective temperature and metallicity derived from SDSS spectra for ~60,000 F- and G-type main-sequence stars (0.2
  • Publication
    The Milky Way Tomography with SDSS. III. Stellar Kinematics
    We study Milky Way kinematics using a sample of 18.8 million main-sequence stars with r 20 and proper-motion measurements derived from Sloan Digital Sky Survey...
  • Publication
    The miniJPAS survey quasar selection - I. Mock catalogues for classification
    In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar...
  • Publication
    The miniJPAS survey quasar selection: V. Combined algorithm
    Aims. Quasar catalogues from narrow-band photometric data are used in a variety of applications, including targeting for spectroscopic follow-up, measurements...
  • Publication
    The miniJPAS survey: Exploring the spatially resolved capabilities of the J-PAS survey with Py2DJPAS
    This work presents Py2DJPAS, a tool developed in Python to automate the analysis of the properties of spatially resolved galaxies in the miniJPAS survey, a 1...
  • Publication
    The miniJPAS survey: Maximising the photo-z accuracy from multi-survey datasets with probability conflation
    We present a new method for obtaining photometric redshifts (photo-z) for sources observed by multiple photometric surveys using a combination (conflation) of...
  • Publication
    The miniJPAS survey: Photometric redshift catalogue
    MiniJPAS is a ∼1 deg 2 imaging survey of the AEGIS field in 60 bands, performed to demonstrate the scientific potential of the upcoming Javalambre-Physics of...
  • Publication
    The miniJPAS survey: star-galaxy classification using machine learning
    Context. Future astrophysical surveys such as J-PAS will produce very large datasets, the so-called "big data", which will require the deployment of accurate...
  • Publication
    The Minimum Description Length Principle and Model Selection in Spectropolarimetry
    It is shown that the two-part minimum description length principle can be used to discriminate among different models that can explain a given observed data set...