Damiano Rosselli
Aix Marseille Univ, CNRS/IN2P3, CPPM, Marseille, France

Abstract
At low redshift, Type Ia supernovae (SNe Ia) peculiar velocities trace the large-scale velocity field and provide a direct way to measure the growth rate of cosmic structures, testing gravity and dark energy models. I present the Field Level Inference Package (FLIP, Ravoux et al. 2025) fast and flexible framework to model correlated PVs to measure the growth-rate, incorporating the velocity divergence power spectrum, redshift-space distortions, and survey geometry. Using realistic LSST supernova simulations and FLIP, I forecast the precision achievable on the growth-rate parameter, showing that LSST will deliver the most accurate measurement from peculiar velocities alone (Rosselli et al. 2025). I also present the new UNITY 1.6 Bayesian framework to jointly constrain cosmic expansion and structure growth.

2025 October 14, 15:00

IA/U.Lisboa
Faculdade de Ciências da Universidade de Lisboa (C8.2.02)
Campo Grande, 1749-016 Lisboa