Forecast for growth-rate measurement using peculiar velocities from LSST supernovae

TL;DR

This paper assesses LSST supernovae's potential to measure the cosmic growth rate using peculiar velocities, demonstrating that with realistic conditions, it can achieve about 10-18% precision in a specific redshift range, aiding cosmological tests.

Contribution

It introduces a maximum-likelihood method to estimate the growth-rate parameter from LSST supernova peculiar velocities, accounting for observational noise and contamination, and evaluates its accuracy under various scenarios.

Findings

LSST can measure $f\sigma_8$ with 10% precision between redshifts 0.02 and 0.14.

Using three tomographic bins, the growth rate can be constrained with errors below 18%.

Contamination below 2% does not bias the growth-rate measurement.

Abstract

In this work, we investigate the feasibility of measuring the cosmic growth-rate parameter, $f\sigma_8$, using peculiar velocities (PVs) derived from Type Ia supernovae (SNe Ia) in the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). We produce simulations of different SN types using a realistic LSST observing strategy, incorporating noise, photometric detection from the Difference Image Analysis (DIA) pipeline, and a PV field modeled from the Uchuu UniverseMachine simulations. We test three observational scenarios, ranging from ideal conditions with spectroscopic host-galaxy redshifts and spectroscopic SN classification, to more realistic settings involving photometric classification and contamination from non-Ia supernovae. Using a maximum-likelihood technique, we show that LSST can measure $f\sigma_8$ with a precision of $10\%$ in the redshift range $ 0.02 < z < 0.14 $ in the most realistic case. Using three tomographic bins, LSST can constrain the growth-rate parameter with errors below $18\%$ up to $z = 0.14$. We also test the impact of contamination on the maximum likelihood method and find that for contamination fractions below $\sim 2\%$, the measurement remains unbiased. These results highlight the potential of the LSST SN Ia sample to complement redshift-space distortion measurements at high redshift, providing a novel avenue for testing general relativity and dark energy models.