# Constraining neutrino mass and dark energy with peculiar velocities and lensing dispersions of Type Ia supernovae

## TL;DR

This paper demonstrates that peculiar velocities and lensing dispersions of Type Ia supernovae can effectively constrain neutrino mass and dark energy parameters, providing a complementary method to existing cosmological surveys.

## Contribution

It introduces a novel approach using supernova peculiar velocities and lensing dispersions to constrain neutrino mass and dark energy, independent of galaxy surveys.

## Key findings

- Can constrain neutrino mass to < 0.31 eV
- Dark energy parameters w0 and wa constrained to 0.02 and 0.18
- Adding velocity info reduces parameter volume by ~33%

## Abstract

We show that peculiar velocities of Type Ia supernovae can be used to derive constraints on the sum of neutrino masses, $\Sigma m_{\nu}$, and dark energy equation of state, $w = w_0+w_a(1-a)$, from measurements of the magnitude-redshift relation, complementary to galaxy redshift and weak lensing surveys. Light from a supernova propagates through a perturbed Universe so the luminosity distance is modified from its homogeneous prediction. This modification is proportional to the matter density fluctuation and its time derivative due to gravitational lensing and peculiar velocity respectively. At low redshifts, the peculiar velocity signal dominates while at high redshifts lensing does. We show that using lensing and peculiar velocity of supernovae from the upcoming surveys WFIRST and ZTF, without other observations, we can constrain $\Sigma m_{\nu} \lesssim 0.31$ eV, $\sigma(w_0) \lesssim 0.02$, and ${\sigma(w_a)} \lesssim 0.18$ ($1-\sigma$ CL) in the $\Sigma m_{\nu}$-$w_0$-$w_a$ parameter space, where all the other cosmological parameters are fixed. We find that adding peculiar velocity information from low redshifts shrinks the volume of the parameter ellipsoid in this space by $\sim 33$%. We also allow $\Omega_{\text{CDM}}$ to vary as well as $\Sigma m_{\nu}$, $w_0$ and $w_a$, and demonstrate how these constraints degrade as a consequence.