Unbiased Bayesian Inference of Peculiar Motions of Galaxies from Type Ia Supernovae Observations
This research introduces an unbiased Bayesian method to estimate galaxy peculiar velocities using Type Ia supernovae data. By treating redshifts as free parameters and using MCMC sampling, the method avoids biases from incorrect cosmological assumptions or local linearity approximations, providing consistent estimates even when peculiar velocities are significant.