Massive stars exploding in a He-rich circumstellar medium. XI. Diverse evolution of five Ibn SNe 2020nxt, 2020taz, 2021bbv, 2023utc and 2024aej
Z.-Y. Wang, A. Pastorello, Y.-Z. Cai, M. Fraser, A. Reguitti, W.-L. Lin, L. Tartaglia, D. Andrew Howell, S. Benetti, E. Cappellaro, Z.-H. Chen, N. Elias-Rosa, J. Farah, A. Fiore, D. Hiramatsu, E. Kankare, Z.-T. Li, P. Lundqvist, P.A. Mazzali, C. McCully, J. Mo, S. Moran

TL;DR
This study analyzes five Type Ibn supernovae, revealing diverse luminosities, spectral features, and progenitor mass-loss histories, advancing understanding of their explosion mechanisms and circumstellar environments.
Contribution
It provides detailed photometric and spectroscopic analysis of five Ibn SNe, highlighting their diverse properties and progenitor mass-loss characteristics, which was previously not comprehensively documented.
Findings
SN 2023utc is the faintest Type Ibn SN discovered.
Spectra show slow evolution with He I emission lines and high initial temperatures.
Ejecta masses are estimated between 1-3 solar masses, with CSM masses up to 1 solar mass.
Abstract
We present the photometric and spectroscopic analysis of five Type Ibn supernovae (SNe): SN 2020nxt, SN 2020taz, SN 2021bbv, SN 2023utc, and SN 2024aej. These events share key observational features and belong to a family of objects similar to the prototypical Type Ibn SN 2006jc. The SNe exhibit rise times of approximately 10 days and peak absolute magnitudes ranging from 16.5 to 19 mag. Notably, SN 2023utc is the faintest Type Ibn supernova discovered to date, with an exceptionally low r-band absolute magnitude of mag. The pseudo-bolometric light curves peak at erg s, with total radiated energies on the order of erg. Spectroscopically, these SNe display relatively slow spectral evolution; the early spectra are characterised by a hot blue continuum and prominent He I emission lines. Early spectra show blackbody…
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.
