Orateur
Description
The Dark Energy Spectroscopic Instrument (DESI) provides highly precise measurements of galaxy clustering. To extract the maximum cosmological information from these datasets, Full-Shape and ShapeFit analyses based on the Effective Field Theory of Large-Scale Structure (EFTofLSS) have become the standard approach. However, marginalizing over a broad parameter space of EFTofLSS nuisance parameters (galaxy bias, counter- and stochastic terms) introduces significant degeneracies that weaken cosmological constraints.
In this talk, I will review recent full-shape and ShapeFit results from DESI, focusing on how these nuisance parameter degeneracies impact current cosmological inference. Finally, I will discuss theoretical avenues aimed at mitigating these limitations. I will outline an approach to higher-order bias featuring environmental dependence, inspired by the web-halo model. By physically conditioning halo formation on the surrounding cosmic web, this framework seeks to provide analytical priors for non-linear biases, offering a potential pathway to break EFTofLSS degeneracies in ongoing and future large-scale structure surveys.