Publications

  • A study of extragalactic planetary nebulae populations based on spectroscopy. I. Data compilation and first findings

    We compile published spectroscopic data and [O III] magnitudes of almost 500 extragalactic planetary nebulae (PNe) in 13 galaxies of various masses and morphological types. This is the first paper of a series that aims to analyse the PN populations and their progenitors in these galaxies. Although the samples are not complete or homogeneous, we

    Delgado-Inglada, G. et al.

    Advertised on:

    9
    2020
  • μ<SUB>⋆</SUB> masses: weak-lensing calibration of the Dark Energy Survey Year 1 redMaPPer clusters using stellar masses

    We present the weak-lensing mass calibration of the stellar-mass-based μ⋆ mass proxy for redMaPPer galaxy clusters in the Dark Energy Survey Year 1. For the first time, we are able to perform a calibration of μ⋆ at high redshifts, z > 0.33. In a blinded analysis, we use ∼6000 clusters split into 12 subsets spanning the ranges 0.1 ≤ z < 0.65 and μ⋆

    Pereira, M. E. S. et al.

    Advertised on:

    9
    2020
  • A precise architecture characterization of the π Mensae planetary system★

    Context. The bright star π Men was chosen as the first target for a radial velocity follow-up to test the performance of ESPRESSO, the new high-resolution spectrograph at the European Southern Observatory's Very Large Telescope. The star hosts a multi-planet system (a transiting 4 M⊕ planet at ~0.07 au and a sub-stellar companion on a ~2100-day

    Damasso, M. et al.

    Advertised on:

    10
    2020
  • Exploring the Stellar Age Distribution of the Milky Way Bulge Using APOGEE

    We present stellar age distributions of the Milky Way bulge region using ages for ∼6000 high-luminosity ( $\mathrm{log}(g)\lt 2.0$ ), metal-rich ([Fe/H] ≥ -0.5) bulge stars observed by the Apache Point Observatory Galactic Evolution Experiment. Ages are derived using The Cannon label-transfer method, trained on a sample of nearby luminous giants

    Hasselquist, Sten et al.

    Advertised on:

    10
    2020
  • The CARMENES search for exoplanets around M dwarfs. A deep learning approach to determine fundamental parameters of target stars

    Existing and upcoming instrumentation is collecting large amounts of astrophysical data, which require efficient and fast analysis techniques. We present a deep neural network architecture to analyze high-resolution stellar spectra and predict stellar parameters such as effective temperature, surface gravity, metallicity, and rotational velocity

    Passegger, V. M. et al.

    Advertised on:

    10
    2020