Type Ia Supernova Peculiar Velocity Inference with the BORG Forward Model Towards ZTF Applications

Abstract

Peculiar velocities of matter tracers, arising from gravitational infall into large-scale structures, can be used to determine the growth rate of cosmic structure, $f\sigma_8$,providing a direct test of General Relativity. Measurements of velocity fields therefore constitute an important probe of the standard cosmological model. In this talk, I will present our methodology based on the *Bayesian Origin Reconstruction from Galaxies* (BORG) framework, a probabilistic forward-modeling approach designed to infer both the initial conditions and the late-time large-scale structures of the Universe. This framework jointly infers the density and peculiar velocity fields. We explore the application of this approach to Type Ia supernovae in order to fully exploit the rich low-redshift ($z<0.1$) supernova dataset provided by the Zwicky Transient Facility (ZTF). Accurate measurements of $f\sigma_8$ at low redshift are particularly informative for tests of gravity, as this is the regime where the effects of cosmic expansion are least dominant. I will present growth rate results from mock catalogues generated within the BORG framework and by the ZTF collaboration. BORG-generated mocks demonstrate accurate recovery of the underlying velocity field and cosmological parameters, while applications to ZTF mock catalogues represent a first step toward a full field-level analysis of peculiar velocities with real supernova samples.