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Centro de Astrofísica da Universidade do Porto
A Bayesian modelling of α Cen A

Michaël Bazot
CAUP

Abstract
α Cen A is the closest star to the Sun and, as such, one of the most extensively studied. For stellar physicists, it remains a interesting subject of debate. In particular the mechanisms governing the transport of energy in the innermost regions of the star have long been debated. In order to understand them properly, it is necessary to use the best observational constraints available to obtain precise values of the global stellar parameters: the mass, the age, the initial chemical composition,... This describes an inverse problem that I will cast in the Bayesian formalism. In order to solve this problem I suggest using Markov Chain Monte Carlo methods. I will show that this approach allows to efficiently constrain the stellar parameters and, as a consequence, to discuss the possibility of convective energy transport at the center of α Cen A.

24 October 2012, 13:30

Centro de Astrofísica
Rua das Estrelas
4150-762 Porto

Institute of Astrophysics and Space Sciences

Institute of Astrophysics and Space Sciences (IA) is a new but long anticipated research infrastructure with a national dimension. It embodies a bold but feasible vision for the development of Astronomy, Astrophysics and Space Sciences in Portugal, taking full advantage and fully realizing the potential created by the national membership of the European Space Agency (ESA) and the European Southern Observatory (ESO). IA resulted from the merging the two most prominent research units in the field in Portugal: the Centre for Astrophysics of the University of Porto (CAUP) and the Center for Astronomy and Astrophysics of the University of Lisbon (CAAUL). It currently hosts more than two-thirds of all active researchers working in Space Sciences in Portugal, and is responsible for an even greater fraction of the national productivity in international ISI journals in the area of Space Sciences. This is the scientific area with the highest relative impact factor (1.65 times above the international average) and the field with the highest average number of citations per article for Portugal.

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