Self-consistent spectral modeling of quasars and its implication to the mass assembly history galaxies


  • Call:

    IDPASC Portugal - PHD Programme 2019

  • Academic Year:

    2019 / 2020

  • Domain:


  • Supervisor:

    Jean Michel Gomes

  • Co-Supervisor:

    Luis Vega

  • Institution:

    Universidade do Porto

  • Host Institution:

    Universidade do Porto

  • Abstract:

    Quasars are thought to be hosted by a supermassive black hole (SMBH) capable of producing an energy release due to matter accretion that easily outshines the whole host galaxy, leading to this featureless quasi-stellar object appearance. This class of extremely luminous Active Galactic Nuclei (AGN) is an excellent laboratory for furnishing tight constraints on the formation and evolution of galaxies since they can be observed at all redshift values. They are also associated with the most massive and luminous galaxies in the early Universe. Over the past few years, it was discovered several quasars even at early times (redshift ~7). We propose a new spectral fitting code for fitting the UV-optical range in a self-consistent manner to be applied to quasars. This code will include a standard accretion disk model (Shakura & Sunyaev 1973) and a more realistic UV-optical model from, e.g., Kubota & Done (2018). We will tie these prescriptions together in order to energetically reproduce both the observed continuum plus emission-lines in quasars considering internal attenuation. This new fitting code will be publicly available and additionally applied to ~500 000 quasars from the SDSS DR15. We will produce a full database catalog for the astronomical community. This is a preparatory work for the MOONS spectrograph in which IA co-leads also it will add value when the modules for fitting quasars are incorporated in the population synthesis code FADO (Gomes & Papaderos 2017). This project provides an excellent combination of astrophysical theory with observations, and it will lead to valuable expertise in the field of spectral synthesis and AGN phenomenon. Several publications will support the future career of the student. Preferable computing languages are Fortran, Python or IDL.