The Bayesian Origin Reconstruction from Galaxies (BORG) algorithm provides a Bayesian framework to recover the dark matter field through forward modeling of structure formation, accounting for the nonlinear evolution of the velocity field. In this talk, I will present applications of BORG to the ZTF DR2.5 supernova sample, as well as results from realistic ZTF supernova simulations,...
We develop a novel approach to constrain the Hubble parameter $H_0$ and the primordial power spectrum amplitude $A_\mathrm{s}$ using type Ia supernovae (SNIa) data. By considering SNIa as tracers of the peculiar velocity field, we can model their distance and their covariance as a function of cosmological parameters without the need of calibrators like Cepheids; this yields a new independent...
The universe we observe today is dotted with galaxy clusters separated by vast voids, in sharp contrast to its initial state, which was nearly uniform with only minor density fluctuations. The evolution from this early uniformity to today's complex structure of galaxies is a profound transformation, with many intermediate processes still unexplained. In this talk, I will explore this...
Invited talk
