The impact of ultraviolet suppression on the rates and properties of strongly lensed Type IIn supernovae detected by LSST

  • Strong Lensing Science Collaboration
  • , Andrés I. Ponte Perez*
  • , Graham P. Smith
  • , Matt Nicholl
  • , Nikki Arendse
  • , Dan Ryczanowski
  • , Suhail Dhawan
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Upcoming wide-field time-domain surveys, such as the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) are expected to discover up to two orders of magnitude more strongly lensed supernovae per year than have so far been observed. Of these, Type IIn supernovae have been predicted to be detected more frequently than any other supernova type, despite their small relative detection fraction amongst non-lensed supernovae. However, previous studies that predict a large population of lensed Type IIn supernova detections model their time evolving spectrum as a pure blackbody. In reality, there is a deficit in the UV flux of supernovae relative to the blackbody continuum due to line-blanketing from iron-group elements in the ejecta and scattering effects. In this work we quantify the effect of this UV suppression on the detection rates by LSST of a simulated population of strongly lensed Type IIn supernovae, relative to a pure blackbody model, using a mock LSST observing run. With a blackbody model, we predict to detect ~70 lensed Type IIn supernova per year with LSST. By modelling a similar UV deficit to that seen in superluminous supernovae, we recover 60–80 per cent of the detections obtained using a pure blackbody model, of which ~10 detections per year are sufficiently bright (⁠mi < 22.5 mag) and detected early enough (> 5 observations before light-curve peak) to enable high-cadence spectroscopic follow up.
Original languageEnglish
Article numberstag009
Number of pages18
JournalMonthly Notices of the Royal Astronomical Society
Volume546
Issue number2
Early online date6 Jan 2026
DOIs
Publication statusPublished - Feb 2026

Keywords

  • gravitational lensing: strong
  • methods: statistical
  • transients: supernovae

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