Peculiar-velocity cosmology with Types Ia and II supernovae

TL;DR

This paper introduces a new supernova dataset and analysis method to measure peculiar velocities and cosmological parameters, providing the tightest $f\sigma_8$ constraint from supernovae to date, including Type II supernovae.

Contribution

The study presents the Democratic Samples of Supernovae (DSS) and a novel snapshot distance method, enabling improved peculiar velocity measurements and cosmological constraints from low-redshift supernovae.

Findings

Measured $f\sigma_8 = 0.390 \pm 0.022$, the tightest from supernovae.

Detected a bulk flow of approximately 195 km/s from beyond the survey volume.

Achieved consistent results with other cosmological measurements.

Abstract

We present the Democratic Samples of Supernovae (DSS), a compilation of 775 low-redshift Type Ia and II supernovae (SNe Ia & II), of which 137 SN Ia distances are derived via the newly developed snapshot distance method. Using the objects in the DSS as tracers of the peculiar-velocity field, we compare against the corresponding reconstruction from the 2M++ galaxy redshift survey. Our analysis -- which takes special care to properly weight each DSS subcatalogue and cross-calibrate the relative distance scales between them -- results in a measurement of the cosmological parameter combination $f\sigma_8 = 0.390_{-0.022}^{+0.022}$ as well as an external bulk flow velocity of $195_{-23}^{+22}$ km s$^{-1}$ in the direction $(\ell, b) = (292_{-7}^{+7}, -6_{-4}^{+5})$ deg, which originates from beyond the 2M++ reconstruction. Similarly, we find a bulk flow of $245_{-31}^{+32}$ km s$^{-1}$ toward $(\ell, b) = (294_{-7}^{+7}, 3_{-5}^{+6})$ deg on a scale of $\sim 30 h^{-1}$ Mpc if we ignore the reconstructed peculiar-velocity field altogether. Our constraint on $f\sigma_8$ -- the tightest derived from SNe to date (considering only statistical error bars), and the only one to utilise SNe II -- is broadly consistent with other results from the literature. We intend for our data accumulation and treatment techniques to become the prototype for future studies that will exploit the unprecedented data volume from upcoming wide-field surveys.