EFFORTS · EFficient search FOR primordial feaTureS in current and future cosmological data

Primordial features (PFs) are scale-dependent deviations from the leading-order, scale-invariant spectra of primordial density perturbations, often manifesting as oscillations. These PFs arise from disturbances in the potential or internal space of primordial Universe models, which alter the background evolution from the leading trajectory. While the amplitudes of these features are uncertain, their presence is likely, and detecting them would offer insights into the physics of the primordial Universe, such as new energy scales and heavier degrees of freedom coupled to the inflaton field. This proposal aims to maximize the efficiency of the search for PFs in current and future cosmological data. I will test PF models against the most recent Cosmic Microwave Background and Large Scale Structure data for the first time using both the power spectrum and bispectrum of primordial fluctuations. At smaller scales, PF signals must be much larger to be detected through the Stochastic Gravitational Wave Background (SGWB) sourced by large scalar fluctuations. Focusing on the future LISA experiment, I will build an efficient code and pipeline to detect these signals in future data. On the theoretical side, I will also explore the contribution of loop corrections in these models, which may dominate over tree-level results, and design novel non-perturbative techniques to compute the spectra in these cases. This project will set the state of the art for analyzing PFs of any amplitude and at any cosmological scales.