The undetectable fraction of core-collapse supernovae in luminous infrared galaxies -- II. GSAOI/GeMS dataset
I. Mäntynen, E. Kankare, S. Mattila, A. Efstathiou, S. D. Ryder + 5 more
TLDR
This study uses GSAOI/GeMS data and Monte Carlo methods to estimate that 86% of core-collapse supernovae in LIRGs are undetectable by optical surveys.
Key contributions
- Used GSAOI/GeMS adaptive optics data from the SUNBIRD survey to monitor nine LIRGs.
- Determined CCSN detection limits using artificial supernova injection and image subtraction.
- Applied Monte Carlo methods to model detection probabilities considering survey cadence and CCSN diversity.
- Found 86% of CCSNe in LIRGs are undetectable by optical surveys, and 54% by near-infrared.
Why it matters
This research refines estimates for the large fraction of core-collapse supernovae hidden by dust in luminous infrared galaxies. Accurately accounting for these undetectable events is vital for determining the true cosmic supernova rates and understanding stellar evolution.
Original Abstract
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. 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. 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. 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.
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