TL;DR
This paper proposes a hierarchical Bayesian method to improve the measurement of the Hubble constant using strongly lensed supernovae by combining magnification data and time delays, promising 1.5% precision with future surveys.
Contribution
It introduces a novel joint inference framework that simultaneously constrains $H_0$, lens mass profiles, and supernova luminosity distributions using both lensed and unlensed supernova data.
Findings
Forecasts 1.5% measurement precision of $H_0$ with 144 glSNe.
Demonstrates the potential of magnification ratios to constrain lens mass profiles.
Highlights the complementarity of supernova magnification and stellar kinematics.
Abstract
The dominant uncertainty in the current measurement of the Hubble constant () with strong gravitational lensing time delays is attributed to uncertainties in the mass profiles of the main deflector galaxies. Strongly lensed supernovae (glSNe) can provide, in addition to measurable time delays, lensing magnification constraints when knowledge about the unlensed apparent brightness of the explosion is imposed. We present a hierarchical Bayesian framework to combine a dataset of SNe that are not strongly lensed and a dataset of strongly lensed SNe with measured time delays. We jointly constrain (i) using the time delays as an absolute distance indicator, (ii) the lens model profiles using the magnification ratio of lensed and unlensed fluxes on the population level and (iii) the unlensed apparent magnitude distribution of the SNe population and the redshift-luminosity relation…
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