Thesis

Parametric stellar convection model for the exploration of helio- and asteroseismic eigenfrequencies properties.

• Call:

  IDPASC Portugal - PHD Programme 2014

• Academic Year:

  2014 /2015

• Domain:

  Astrophysics

• Supervisor:

  Michael Bazot

• Co-Supervisor:

  Mario J. P. F. G. Monteiro

• Institution:

  Universidade do Porto

• Host Institution:

  Centro de Astrofísica da Universidade do Porto

• Abstract:

  Helioseismology and asteroseismology are powerful observational methods that allow to drill the interiors of stars. Measuring oscillation frequencies allows one to constrain theoretical stellar models, i.e. estimate the mass of a star, its age, initial chemical composition or other related physical characteristics. The use of observational constraints sensitive to its interior is of the uttermost importance since i) some fundamental characteristics (e.g. the mass or the age) are mostly determined by the central physical state of the star, ii) the modelling of the surface layers is difficult and our models are much cruder (and hence unlikely to reproduce observations depending mostly on these regions). This second issue is at the heart of a long-standing problem in helio- and asteroseismology. Even though the stellar oscillations are sensitive to the stellar interior, they are still affected by the surface layers. It has long been recognized that there exist systematic differences between computed frequencies, based on our best solar models, and observed solar frequencies. It is this issue we want to investigate in this program. Since it is believed that these differences arise from an improper treatment of the upper layers (top of the surface convective zone, interior/atmosphere boundary, atmosphere) of stars, we want to test alternative physical models that might reinstate an agreement between theory and observations. This would in turn be extremely useful in order to calibrate properly theoretical models using solar data and then apply them to other stars. It has been often conjectured that the current modelling of convection could be the most important factor leading to the exiting disagreement. Therefore, we will explore some parametric models for convection that will allow to tune finely the efficiency of the process, as well as its characteristic length scales. To that effect, we will use Bayesian computational methodologies in order to explore the multi-dimensional spaces of parameter underlying these convection models.