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ASD Colloquium (Hybrid)



New Avenues for Multi-Messenger Discoveries in High Energy Astrophysics
Rafael Martinez-Galarza (CfA, Harvard)

As high-energy datasets enter the era of big data, in particular in the context of multi-messenger astrophysics, we are starting a new chapter in observational X-ray astronomy: time-dependent flux variability of astronomical sources is revealing the nature of new, exotic types of event, such as pair-instability supernovae and neutron star mergers, lensing events, exotic planetary transits, as well as other, yet to be understood phenomena. These phenomena are typically observed over a broad range of wavelengths. Yet, while time-domain surveys at optical wavelengths have taken the lead to profit from vast observational programs (e.g. Vera Rubin), and from an even larger set of machine learning (ML) tools to pick up the exotic sources among millions of regular objects, the X-ray community is only now starting to delve into the synergies between data science and large data astronomical datasets for discovery. In this talk I will provide an overview of recent developments in data-driven, time-domain X-ray astronomy, and will attempt to provide an answer to the question “Which avenues of inquiry will be most ripe for discovery in the next few years?”. I will present a framework for the treatment of large X-ray datasets for the discovery of relevant transients, and present novel data representations for the event files that allow for their seamless discovery. I will show how these representations can be used in combination with ML architectures such as autoencoders, dimensionality reduction, and Graph Neural Networks to enable new science in the era of multi-messenger astrophysics. As a demonstration, I will share recent results on X-ray binary classification, and searches for fast X-ray transients in Chandra data.

Date March 07, 2023
Start/End Time 03:45 PM - 05:00 PM
Location B34, W150 and Teams
Contact Scott Noble
Email Address
Event Type Seminars/Colloquia
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