The undetectable fraction of core-collapse supernovae in luminous infrared galaxies

II. GSAOI/GeMS dataset

¹ Tuorla Observatory, Department of Physics and Astronomy, University of Turku, 20014 Turku, Finland
² School of Sciences, European University Cyprus, Diogenes street, Engomi, 1516 Nicosia, Cyprus
³ School of Mathematical and Physical Sciences, Macquarie University, Sydney, NSW 2109, Australia
⁴ Astrophysics and Space Technologies Research Centre, Macquarie University, Sydney, NSW 2109, Australia
⁵ Cosmic Dawn Center (DAWN)
⁶ Niels Bohr Institute, University of Copenhagen, Jagtvej 128, 2200 Kóbenhavn N, Denmark
⁷ Finnish Centre for Astronomy with ESO (FINCA), University of Turku, 20014 Turku, Finland
⁸ South African Astronomical Observatory, P.O. Box 9, Observatory, 7935 Cape Town, South Africa

^★ Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 18 December 2025
Accepted: 3 April 2026

Abstract

Context. Core-collapse supernovae (CCSNe) in luminous infrared galaxies (LIRGs) can have extreme line-of-sight host galaxy dust extinctions, which leads to a large fraction of the events remaining undetected by optical and infrared surveys. This population of undetected CCSNe is important to constrain in order to determine the cosmic CCSN rates, which can be used to estimate the cosmic star formation history independently from methods based on galaxy luminosities.

Aims. Our aim is to confirm and refine our estimates for the undetectable fraction of CCSNe in LIRGs in the local Universe. Our study is based on the near-infrared K-band multi-epoch SUNBIRD survey monitoring dataset of a sample of nine LIRGs using the Gemini-South telescope with the multi-conjugate GSAOI/GeMS laser guide star adaptive optics system.

Methods. We determined the limiting magnitudes for CCSN detection for each epoch in our dataset with artificial supernova injection and image subtraction methods. Subsequently, we used a Monte Carlo method to determine the combined effects of limiting magnitudes, survey cadence, CCSN subtype distribution, and their light curve evolution diversity. The intrinsic CCSN rates of the sample galaxies were estimated based on detailed modelling of their spectral energy distribution. Finally, we combined the resulting CCSN detection probabilities with the intrinsic CCSN rates for the dataset, and compared that against the real CCSN detections over the survey period.

Results. Based on our GSAOI/GeMS dataset, assuming optical or near-infrared example surveys with capabilities to detect CCSNe in local LIRGs with host extinctions of A_V = 3 or 16 mag, respectively, the resulting total undetectable fractions are 86.0^+4.7_−5.9% and 53.6^+15.6_−19.6%. When folding in the results from our previous near-infrared adaptive optics assisted LIRG monitoring dataset, the corresponding total undetectable fractions are 88.3^+2.6_−3.2% and 61.4^+8.5_−10.6%, respectively.