Detectability of Gravitationally Lensed Kilonovae in the Rubin LSST
Anindya Ganguly, Anupreeta More

TL;DR
This paper simulates and analyzes the detectability of gravitationally lensed Kilonovae in LSST data, highlighting how their color evolution and lensing magnification influence detection rates.
Contribution
It introduces the first realistic simulation of lensed KNe populations in LSST, examining how merger delay times affect detection probabilities.
Findings
KNe color evolution differs from Type Ia Supernovae, aiding identification.
Detection rates increase with longer merger delay times and shallower delay time distribution slopes.
Magnification thresholds for detecting specific events at redshifts 0.5 and 1.0 are quantified.
Abstract
Identification and characterisation of Kilonovae (KNe) can be instrumental in improving our understanding of cosmology and astrophysics. However, their detection poses unique challenges due to rarity and faintness. Upcoming telescopes, with their deep imaging capabilities and wide field-of-views, will provide a unique opportunity to observe these rare and faint transients. The Rubin Legacy Survey of Space and Time (LSST) will generate a deluge of data, making it essential to deploy fast, efficient methods for identifying genuine KNe, especially when they are gravitationally lensed. To address this, we simulate realistic populations of both unlensed and lensed KNe in the six LSST bands. Comparing with the Type Ia Supernovae, we find that the KNe color evolution is more rapid and the two separate out when their colors are compared at two epochs. Since the mergers of compact binaries are…
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