TAP Colloquium: More Pixels, More Stars, More Physics: Probing Late-Stage Massive Star Evolution with Cutting-Edge Datasets

Abstract: As individual objects, evolved massive stars are laboratories in which to probe the unconstrained physics of stellar evolution. En masse, they have an outsized impact on their host galaxies through their high luminosities, strong winds, and in particular, their terminal supernova explosions. Despite this importance, evolved massive stars -- in which our uncertainties in convection, winds, interactions with binary companions, and more are most amplified -- are also the poorest studied due to limitations in sample sizes. In this talk, I will present my recent work that utilizes machine learning and Gaia DR3 spectroscopy to compile a high-resolution portrait of the HR diagram of cool supergiants in the Large Magellanic Cloud. Drawing connections with my previous work on the variability of evolved massive stars, I will show that these data point the way to a more complete understanding of the physics of massive star evolution, and further bridge the gap between massive stars and the core collapse events they produce.

Bio: 

Trevor is a Carnegie Fellow at the Carnegie Observatories where he leverages cutting- edge datasets to study the evolution of massive stars from ZAMS to core collapse. His work touches on time domain methods, astrostatistics, population synthesis, spectroscopy from R=50-50000, machine learning, and more. He is a proud alumnus of Wesleyan University (2015) and the University of Washington (2021). Outside of work, he is a baker, a musician, a coffee snob, and the co-owner of the world's grumpiest dachshund. 

Meet the speaker: Contact the host, Mathieu Renzo or

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Reception: Refreshments at 3:00 PM, Kuiper Building, 3rd Floor Atrium 

Live stream: Zoom Meeting ID: 417 674 3144   Passcode: 1985ASTRO