Zooming In on the Progenitors of Superluminous Supernovae With the HST
R. Lunnan, R. Chornock, E. Berger, A. Rest, W. Fong, D. Scolnic, D., Jones, A. M. Soderberg, P. M. Challis, M. R. Drout, R. J. Foley, M. E. Huber,, R. P. Kirshner, C. Leibler, G. H. Marion, M. McCrum, D. Milisavljevic, G., Narayan, N. E. Sanders, S. J. Smartt, K. W. Smith

TL;DR
This study uses HST ultraviolet imaging to analyze the host galaxies of hydrogen-poor superluminous supernovae, revealing their irregular, compact nature and suggesting they form in dense, star-forming environments, with progenitors possibly differing from those of LGRBs.
Contribution
First detailed HST UV imaging of SLSN host galaxies, characterizing their morphology, star formation, and SN locations to understand progenitor environments.
Findings
Host galaxies are irregular, compact dwarf galaxies with median radius 0.9 kpc.
SLSNe occur in high star formation density regions, indicating dense environments.
SN locations are intermediate in clustering between LGRBs and normal SNe.
Abstract
We present Hubble Space Telescope (HST) rest-frame ultraviolet imaging of the host galaxies of 16 hydrogen-poor superluminous supernovae (SLSNe), including 11 events from the Pan-STARRS Medium Deep Survey. Taking advantage of the superb angular resolution of HST, we characterize the galaxies' morphological properties, sizes and star formation rate (SFR) densities. We determine the supernova (SN) locations within the host galaxies through precise astrometric matching, and measure physical and host-normalized offsets, as well as the SN positions within the cumulative distribution of UV light pixel brightness. We find that the host galaxies of H-poor SLSNe are irregular, compact dwarf galaxies, with a median half-light radius of just 0.9 kpc. The UV-derived SFR densities are high (<Sigma_SFR> ~ 0.1 M_sun/yr/kpc^2), suggesting that SLSNe form in overdense environments. Their locations trace…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
