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Title: Dust masses for a large sample of core-collapse supernovae from optical emission line asymmetries: dust formation on 30-year time-scales
ABSTRACT Modelling the red–blue asymmetries seen in the broad emission lines of core-collapse supernovae (CCSNe) is a powerful technique to quantify total dust mass formed in the ejecta at late times (>5 yr after outburst) when ejecta dust temperatures become too low to be detected by mid-infrared (IR) instruments. Following our success in using the Monte Carlo radiative transfer code damocles to measure the dust mass evolution in SN 1987A and other CCSNe, we present the most comprehensive sample of dust mass measurements yet made with damocles, for CCSNe aged between 4 and 60 yr after outburst. Our sample comprises multi-epoch late-time optical spectra taken with the Gemini/Gemini Multi-Object Spectrographs (GMOS) and Very Large Telescope (VLT) X-Shooter spectrographs, supplemented by archival spectra. For the 14 CCSNe that we have modelled, we confirm a dust mass growth with time that can be fit by a sigmoid curve that is found to saturate beyond an age of ∼30 yr, at a mass of 0.23$$^{+0.17}_{-0.12}$$ M⊙. For an expanded sample including dust masses found in the literature for a further 11 CCSNe and six CCSN remnants, the dust mass at saturation is found to be 0.42$$^{+0.09}_{-0.05}$$ M⊙. Uncertainty limits for our dust masses were determined from a Bayesian analysis using the affine invariant Markov chain Monte Carlo ensemble sampler emcee with damocles. The best-fitting line profile models for our sample all required grain radii between 0.1 and 0.5 $$\mu$$m. Our results are consistent with CCSNe forming enough dust in their ejecta to significantly contribute to the dust budget of the Universe.  more » « less
Award ID(s):
2037297 1914448
PAR ID:
10369279
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ;
Publisher / Repository:
Oxford University Press
Date Published:
Journal Name:
Monthly Notices of the Royal Astronomical Society
Volume:
515
Issue:
3
ISSN:
0035-8711
Page Range / eLocation ID:
p. 4302-4343
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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