Find the haystacks, then look for needles: the rate of strongly lensed supernovae in galaxy–galaxy strong gravitational lenses

ABSTRACT The time-delay between appearances of multiple images of a gravitationally lensed supernova (glSN) is sensitive to the Hubble constant, $H_0$. As well as time-delays, a lensed host galaxy is needed to enable precise inference of $H_0$. In this work, we investigate the connection between discoverable lensed transients and their host galaxies. We find that the Legacy Survey of Space and Time (LSST) will discover at least 90 glSNe per year, of which 54 per cent will also have a strongly lensed host. The rates are uncertain by approximately 30 per cent depending primarily on the choice of the unlensed SN population and uncertainties in the redshift evolution of the deflector population, but the fraction of glSNe with a lensed host is consistently around a half. LSST will discover around 20 glSNe per year in systems that could plausibly have been identified by Euclid as galaxy–galaxy lenses before the discovery of the glSN. Such systems have preferentially longer time-delays and therefore are well suited for cosmography. We define a golden sample of glSNe Ia with time-delays over 10 d, image separations greater than 0.8 arcsec, and a multiply imaged host. For this golden sample, we find 91 per cent occur in systems that should already be discoverable as galaxy–galaxy lenses in Euclid. For cosmology with glSNe, monitoring Euclid lenses is a plausible alternative to searching the entire LSST alert stream.

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Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2024-11-05
DOI
https://doi.org/10.1093/mnras/stae2486
Citations
14
Primary Topic
Gamma-ray bursts and supernovae
Type
article
Field-Weighted Citation Impact
4.64

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article

Find the haystacks, then look for needles: the rate of strongly lensed supernovae in galaxy–galaxy strong gravitational lenses

Dan Ryczanowski, Martine Lokken, Wolfgang Enzi, M. Magee et al.
14 citations
Monthly Notices of the Royal Astronomical Society
Gamma-ray bursts and supernovae
4.64
article

Find the haystacks, then look for needles: the rate of strongly lensed supernovae in galaxy–galaxy strong gravitational lenses

Dan Ryczanowski, Martine Lokken, Wolfgang Enzi, M. Magee, Thomas E. Collett, Ana Sainz de Murieta, Justin D. R. Pierel, Alex Gagliano
article en
14 citations

Abstract

ABSTRACT The time-delay between appearances of multiple images of a gravitationally lensed supernova (glSN) is sensitive to the Hubble constant, $H_0$. As well as time-delays, a lensed host galaxy is needed to enable precise inference of $H_0$. In this work, we investigate the connection between discoverable lensed transients and their host galaxies. We find that the Legacy Survey of Space and Time (LSST) will discover at least 90 glSNe per year, of which 54 per cent will also have a strongly lensed host. The rates are uncertain by approximately 30 per cent depending primarily on the choice of the unlensed SN population and uncertainties in the redshift evolution of the deflector population, but the fraction of glSNe with a lensed host is consistently around a half. LSST will discover around 20 glSNe per year in systems that could plausibly have been identified by Euclid as galaxy–galaxy lenses before the discovery of the glSN. Such systems have preferentially longer time-delays and therefore are well suited for cosmography. We define a golden sample of glSNe Ia with time-delays over 10 d, image separations greater than 0.8 arcsec, and a multiply imaged host. For this golden sample, we find 91 per cent occur in systems that should already be discoverable as galaxy–galaxy lenses in Euclid. For cosmology with glSNe, monitoring Euclid lenses is a plausible alternative to searching the entire LSST alert stream.

Monthly Notices of the Royal Astronomical SocietyVol. 535(3)
Space Telescope Science Institute (US), Institute for High Energy Physics (ES), University of Warwick (GB), Center for Astrophysics Harvard & Smithsonian (US), The NSF AI Institute for Artificial Intelligence and Fundamental Interactions (US), Institute of Science and Technology, University of Portsmouth (GB)
National Science Foundation, University of Warwick, European Commission, H2020 European Research Council
Openalex Percentile: Top 5%
Gamma-ray bursts and supernovae
4.64
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