Cosmologie

The covariance of galaxy clusters is an important element when constraining cosmology with galaxy clusters. However its computation is costly in computational resources, especially when it depends on cosmology. We propose an evaluation of the impact on the cosmological parameters when the modeling of the cluster covariance is simplified. This is one of the projects for the preparation of the LSST-DESC cluster cosmology framework.
The 21 cm HI transition offers a window onto the reionization history of the universe and the formation of the first generation of stars and quasars, when the universe was still metal poor. The global 21 cm signal consists of the non-Galactic distortion of the CMB blackbody radiation through absorption or emission by HI (atomic hydrogen) depending on whether the HI spin temperature is less or greater than the CMB temperature. Recently the EDGES experiment has detected a large signal that appears incompatible with existing theoretical models.
Machine Learning techniques have revolutionized artificial intelligence. Their application to astrophysics and cosmology permits us to analyze the large quantity of data obtained with current surveys and expected from future surveys with the aim of improving our understanding of the cosmological model.
The primary objective of cosmological research in the coming decade is to understand the accelerated expansion of the Universe, attributed to either a dark energy component or a modification to gravity on cosmic scales.  This thesis will focus on evaluating the Euclid galaxy cluster selection function, an essential element of using the mission’s cluster catalog as a probe of dark energy and modified gravity.