Speaker
Description
In the evolving landscape of modern precision cosmology, the continuous progress of ongoing and upcoming surveys has provided us an unprecedented level of statistical power. Throughout my doctoral journey, I have mostly explored the Cosmic Microwave Background (CMB) at small angular scales, seeking to constrain cosmological parameters. My research has been dedicated to the development of robust and optimal estimators, poised to play a crucial role in current and future CMB surveys. In the first part, I will discuss how the motion of our observation frame impacts CMB fluctuations, specifically through aberration and modulation effects. These subtle effects at the smaller scales, violate the statistically isotropic nature of the CMB, and can be captured in the off-diagonal terms of the CMB covariance matrix in harmonic space. In a Bayesian approach, we have estimated our observation frame's motion from the Planck-2018 temperature data employing the Hamiltonian Monte Carlo (HMC) sampling technique. In the second part, I will explore the utilization of the CMB in probing galaxy clusters, which are the largest collapsed structures in the universe. What we are really curious about is figuring out how many of these clusters exist at different masses and ages (redshifts). But measuring their mass is not straightforward. So, we use the weak gravitational lensing of CMB to estimate how massive these clusters really are. In this talk, I present the power of the Maximum-a-posteriori (MAP) method, showcasing its enhanced precision in measuring cluster masses compared to traditional quadratic estimators (QE), for the upcoming CMB-Stage 4 experiment.
