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Teaser, summary, work performed and final results

Periodic Reporting for period 2 - SNDUST (Supernova dust: production and survival rates)

Teaser

Summary

The problem being addressed by SNDUST 694520 is the origin of the dust
component of the Universe, and specifically whether core-collapse
supernovae (CCSNe), produced by massive stars, are the main sources of the
interstellar dust found in galaxies.

The relevance of the SNDUST project for society is that interstellar dust
is the source of the solid material that is incorporated into planets
during the star formation process, as well as into lifeforms found on
planets. Just as the origin of the elements is relevant to society, so
also is the origin of the dust component of the Universe out of which life
formed.

The objectives of the project are (A) (Theme 1) to determine
observationally the quantities of dust formed by CCSNe, via optical and
infrared observations of the gas and dust in supernova ejecta having ages
ranging from a few hundred days to a few hundred years after the supernova
events that produced them; (B) (Theme 2) to study theoretically the
survivability of dust particles formed in supernova ejecta against
destruction in reverse shocks caused by sputtering by gas particles and by
grain-grain collisions, with the aim of determining the fraction of newly
formed supernova dust particles that are injected into the interstellar
medium of galaxies.

Work performed

\"Theme 1 (To determine observationally the quantities of dust formed by supernovae):
Papers in Theme 1 that have been published by the SNDUST team include:

(1) Determination of the dust mass in the 340-yr old supernova remnant Cassiopeia A:
(a) from a multi-component dust analysis that used Herschel, Planck and Spitzer space
telescope infrared and submillimetre data (Ref. 2; De Looze et al. 2017, MNRAS), and
(b) from a separate analysis of the dust content of Cas A and of two other supernova
remnants published by Bevan et al. (Ref. 3; 2017, MNRAS) that utilised the Monte Carlo
dust radiative transfer code DAMOCLES (Bevan & Barlow 2016, MNRAS) to model the
red-blue emission line asymmetries in the integrated optical spectra of these remnants.
Satisfying agreement was found between the dust mass estimates obtained using these
two entirely different methods (between 0.5-1.1 solar masses of dust in Cas A).

(2) Studies of dust and molecules in Supernova 1987A:
(a) The paper \"\"ALMA spectral survey of Supernova 1987A - molecular inventory, chemistry,
dynamics and explosive nucleosynthesis\"\" (Ref. 1; Matsuura et al. MNRAS, 469, 3347, 2017)
reports the detection in the 30-year old ejecta of Supernova 1987A of several cold molecular
species, including CO, SiO and HCO+. The detection of 12CO, 13CO and 28SiO, and upper
limits for 29SiO and 30SiO, have enabled isotopic studies of supernova nucleosynthesis
products to be carried out for the first time.
(b) The paper \"\"SOFIA mid-infrared observations of Supernova 1987A in 2016 - forward shocks
and possible dust re-formation in the post-shocked region\"\" (Ref. 13; Matsuura et al. MNRAS,
482, 1715, 2019) reports that the mid-infrared 31.5-micron flux measured with NASA\'s SOFIA
Airborne Observatory in 2016 from SN 1987A\'s equatorial Ring is significantly larger than
measured with the Spitzer Space Telescope ten years previously. The dust mass in the
Ring is found to be ten times larger than measured earlier, indicating grain re-formation
and growth in the post-shock region following the impact on the Ring of the supernova
ejecta.

(3) Observations and modelling of supernova red-blue emission line asymmetries:
Fifty hours of Very Large Telescope time at Priority A were allocated
during ESO Semester P97, carrying over into Semester P98 (up to March 31st
2017), enabling between two to three deep X-Shooter optical and near-IR
spectra to be obtained for each of twenty-three core-collapse supernova
ejecta with ages of between 5 and 60 years after outburst. A further
20 hours of X-Shooter time has been allocated in ESO Semester P103,
enabling a further eight targets to be observed. The analysis of
red-blue emission line asymmetries seen in these spectra is being
undertaken using the Monte Carlo dust radiative transfer code DAMOCLES
(Bevan & Barlow 2016, MNRAS) in order to derive the quantities of dust
present in the ejecta at each epoch of observation. A paper on the
use of Bayesian methods for finding optimum fits to dust-affected emission
line profiles has been published by A. Bevan (Ref. 11; MNRAS, 2018), while
the first paper on modelling results and dust mass estimates, for SN 2005ip,
has been submitted to MNRAS by Bevan et al. (2019, arxiv.org/abs/1809.09055).

Theme 2: (To study theoretically the survivability of dust particles formed in
supernova ejecta against destruction in reverse shocks):

For this theme, originally planned to start in Year 2 of the grant, PhD student
F. Schmidt commenced on October 1st 2016, whilst postdoctoral
research fellow F. Kirchschlager commenced on May 2nd 2017.
An initial period was spent benchmarking and assessing a number of publicly
available hydrodynamical/MHD numerical codes, including ENZO, PLUTO
and AstroBEAR, for their suitability to model grain destruction by shocks in
supernova shock fronts. A final choice was made to use the AstroBEAR code
(http://ascl.net/1104.002). Good progress has been made since then, initially
wit\"

Final results

\"In her paper \"\"Measuring dust in core-collapse supernovae with a Bayesian approach to line profile modelling\"\" (Ref. 11, MNRAS, 480, 4659, 2018; arxiv.org/abs/1803.10241), A. Bevan has applied Bayesian methods to the DAMOCLES Monte Carlo line radiative transfer code, which models the extent and shape of dust-affected supernova line profiles to determine the dust mass that has condensed, in addition to other properties of the dusty ejecta. Specifically, the paper presents the application of an affine invariant Markov Chain Monte Carlo ensemble sampler (EMCEE) to the DAMOCLES code in order to investigate the multidimensional parameter space rigorously and characterize the posterior probability distribution. A likelihood function is formulated that handles both Monte Carlo and observational uncertainties. This Bayesian approach was applied to four simulated line profiles in order to test the method and investigate its efficacy. The majority of parameters can be tightly constrained using this method, and a strong (predictable) dependence between the grain size and the dust mass is quantified.\"