Speaker: Virginia Ajani
Title: Cosmological parameter estimation and new higher-order statistics methods for weak lensing
Abstract: Modeling the effect of massive neutrinos on the background evolution of the Universe and the growth of structure is one of the key challenges in modern cosmology. Weak-lensing cosmological constraints will also soon reach higher levels of precision with next-generation galaxy surveys like Euclid. To extract the non-Gaussian cosmological information encoded in cosmic shear data, one needs to go beyond second order statistics as the weak lensing power spectrum. In this talk, I will present some advantages of multi-scale filtering techniques when performing inference on cosmological parameters with higher-order statistics computed on simulated weak lensing convergence maps as input data. To illustrate this, I will show the impact on cosmological constraints of a starlet filter and a multi-Gaussian filter applied on noisy convergence maps generated from the Cosmological Massive Neutrino Simulations (MassiveNuS) when employing peak counts, and I will present a new proposed weak lensing statistics called the “starlet l1-norm” that shows promising properties for cosmological parameter inference.
Topic: Tuesday Lunch Talk
Date: Jan 12, 2021 11:56 AM London