AstroAI Lunch Talks - July 29, 2024 - Ethan Tregidga
29 Jul 2024 - Joshua Wing
The video can be found here: https://www.youtube.com/watch?v=3_-JBEk-Pao
Speaker: Ethan Tregidga
Title: X-ray Spectral Fitting with Autoencoders
Abstract: Black hole X-ray binaries (BHBs) offer insights into extreme gravitational environments and the testing of general relativity. The X-ray spectrum collected by NICER offers valuable information on the properties and behaviour of BHBs through spectral fitting. However, traditional spectral fitting methods are slow and scale poorly with model complexity. We developed a new semisupervised autoencoder neural network for parameter prediction and spectral reconstruction of BHBs, showing significant improvements in speed while maintaining comparable accuracy. The approach maps the spectral features from the numerous outbursts catalogued by NICER and generalizes them to new systems for efficient and accurate spectral fitting. The effectiveness of this approach is demonstrated in the spectral fitting of BHBs and holds promise for use in other areas of astronomy and physics for categorizing large data sets.
Watch the talk below!