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SUMMARY:Type Ia supernovae: Constraining thermonuclear explosion physics w
 ith machine learning - Mark Magee (University of Warwick)
DTSTART:20240508T124000Z
DTEND:20240508T130500Z
UID:TALK216697@talks.cam.ac.uk
CONTACT:Hannah Uebler
DESCRIPTION:Type Ia supernovae are thermonuclear explosions of white dwarf
 s in binary systems. They play an important role in many areas of astrophy
 sics\, from providing chemical enrichment for galaxies to acting as cosmol
 ogical distance probes. In spite of this\, we still fundamentally do not k
 now how or why some white dwarfs explode as thermonuclear supernovae. Mult
 iple explosion mechanisms have been proposed\, but the computational expen
 se associated with developing realistic explosion simulations and the diff
 iculty in observing key diagnostic signatures mean that providing robust c
 onstraints on the explosion physics is challenging. In this talk\, I will 
 provide a general overview of thermonuclear explosion physics and discuss 
 the main explosion scenarios suggested in the literature. I will present m
 y recent work focused on using machine learning to automatically fit spect
 ral sequences of type Ia supernovae in a much more quantitative and effici
 ent way than existing methods. With automated fitting we can test differen
 t explosion scenarios against observations and statistically determine whi
 ch scenario provides the best overall agreement. As spectroscopic samples 
 of supernovae continue to grow\, automated fitting tools will become incre
 asingly important to maximise the physical constraints that can be gained 
 in a quantitative and consistent manner.
LOCATION:The Hoyle Lecture Theatre + Zoom 
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