Séminaire Doctorants / Seminar PhD students |
| « Bayesian Inference in Cosmology » |
|
Doogesh Kodi-Ramanah |
| We will begin with a brief review of the conceptual and philosophical underpinnings of the Bayesian statistical approach, in contrast to the traditional frequentist approach, to illustrate the key features of Bayesian probability theory as a quantitative basis for logical reasoning. We will discuss certain aspects of CMB data analysis, such as map-making and power spectrum estimation. Then we will present an overview of our current work involving the development of a large-scale Bayesian inference framework to constrain cosmological parameters using galaxy redshift surveys, via an application of the Alcock-Paczynski (AP) test. This is a self-consistent hierarchical approach that exploits the full complexity of galaxy redshift surveys. I will also provide a brief description of the AP effect, as a cosmological test of the expansion of the Universe and its geometry. |
|
mercredi 5 avril 2017 - 17:00 Salle Entresol Daniel Chalonge, Institut d'Astrophysique |
| Page web du Séminaire / Seminar's webpage |