Searching for cosmological B-modes in the presence of astrophysical contaminants and instrumental effects - Soutenance

PhD defence of Clara Vergès

Abstract
Cosmology has known a considerable surge in the past twenty years and is now well established as a precision science. Accurate measurements of temperature anisotropies of the Cosmic Microwave Background (CMB) opened an unprecedented window on the primordial Universe. Furthermore, the existing measurements of CMB polarisation anisotropies have confirmed our understanding of early universe physics, and provided important consistency tests of the currently popular models. The next frontier in CMB science is the precise mapping of polarisation anisotropies, and the detection of a specific signature in the polarisation signal, the primordial B-modes. These observations will allow us to push further our knowledge of the Universe and its best-kept secrets, such as dark energy, dark matter and inflation.
 
This detection is particularly challenging, as the signal we look for is very low, and shadowed by various sources of galactic and extra-galactic contamination: polarised dust, synchrotron radiation and weak gravitational lensing - to name a few. The next generation of CMB polarisation experiments therefore needs not only to reach an unprecedented raw instrumental sensitivity, but also to be able to distinguish the signal from these contaminations. This calls for enhanced detection capabilities, new technologies, as well as novel data analysis methods. 
 
This work focuses on understanding whether this increased complexity of CMB experiments will effectively lead to better performances, and at which cost regarding the control of systematic effects. I develop new, involved data models taking into account various instrumental parameters to ensure a better modelling of instrumental systematic effects, in the context of new generation CMB polarisation experiments - POLARBEAR/Simons Array and the Simons Observatory. To prepare for future experiments, I propose an extension of component separation forecasting framework to take into account instrumental systematic effects. I demonstrate its capabilities as a key tool for forecasting the performance of future experiments, and inform calibration strategies to achieve the required performance.

The work under the supervision of Radek Stompor and Josquin Errard.
Zoom link

Dates: 

Friday, 18 September, 2020 - 15:00 to 17:00

Localisation / Location: 

APC
  • Soutenance de thèse

Equipe(s) organisatrice(s) / Organizing team(s): 

  • Autre