Astrophysics

The Effective Field Theory of Large Scale Structure (EFTofLSS) has found tremendous success as a perturbative framework for the evolution of large scale structure, and it is now routinely used to compare theoretical predictions against cosmological observations. The model for the total matter field includes one nuisance parameter at 1-loop order, the effective sound speed, which can be extracted by matching the EFT to full N-body simulations. In this talk we explore two different directions related to the effective sound speed. We first show that its emergence can be understood even without effective field theory ingredients, through a perturbative framework that solves the Vlasov-Poisson system of equations directly in phase space. However, we will argue that the EFT is necessary to ensure self-consistency. We then discuss how one can estimate the effective sound speed, via separate universe techniques, with analytic calculations. The estimate is in good agreement with simulation results, and we show it can be used to extract the cosmology dependence of the effective sound speed and to shed light on what cosmic structures shape its value.

Improving cosmological constraints from galaxy clustering presents several challenges, particularly in extracting information beyond the power spectrum due to the complexities involved in higher-order n-point function analysis. In this talk, I will introduce novel inference techniques that allow us to go beyond the state-of-the-art, not only by utilizing the galaxy trispectrum, a task that remains computationally infeasible with traditional methods, but also by accessing the full information encoded in the galaxy density field for the first time in cosmological analysis. I will present simulation-based inference (SBI), a powerful deep learning technique that enables cosmological inference directly from summary statistics in simulations, bypassing the need for explicit analytical likelihoods or covariance matrices. This is achieved using LEFTfield, a Lagrangian forward model based on the Effective Field Theory of Large Scale Structure (EFTofLSS) and the bias expansion, ensuring robustness on large scales. Furthermore, LEFTfield enables field-level Bayesian inference (FBI), where a field-level likelihood is used to directly analyze the full galaxy density field rather than relying on compressed statistics. I will conclude by exploring the question of how much cosmological information can be extracted at the field level through a comparison of σ8 constraints obtained from FBI, which directly uses the 3D galaxy density field, and those obtained from n-point functions via SBI.

Deviations from a parity-symmetric Universe would strongly signal the presence of new physics beyond the Standard Model. The lowest-order scalar observable sensitive to parity in a homogeneous and isotropic Universe is the connected four-point function of a given cosmological field. Geometrically, this function is described by a suitable average of this field over many tetrahedral configurations. As the CMB represents a spherical projection of three-dimensional curvature fluctuations, its four-point function serves as a unique, but potentially limited, probe of this fundamental symmetry. In this talk, I will discuss progress in rigorously understanding the CMB’s sensitivity to parity-violating physics from both early- and late-time sources.