Spectral classification of white dwarfs by dimensionality reduction

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• Xander Byrne, IoA
• Wednesday 09 October 2024, 13:15-13:40
• The Hoyle Lecture Theatre + Zoom .

If you have a question about this talk, please contact Xander Byrne.

As a suite of large-sky spectroscopic surveys comes online, automated spectral classification techniques are needed more than ever. For white dwarfs—the evolutionary endpoint of the vast majority of stars—spectral classification is vital for understanding their properties, yet still almost exclusively done by eye. Upcoming surveys will return of order 10^5 white dwarf spectra, highlighting the need for automated tools that are fast, but do not miss rare or unique objects, as supervised machine learning models often do. We present the use of dimensionality reduction, an unsupervised method, on white dwarf spectra from the DESI EDR . I will outline the theory behind dimensionality reduction, as well as results showing its effectiveness in classifying white dwarf spectra. I will also discuss two extensions of the technique: the highlighting of spectral regions, and its use in a pseudo-supervised manner.

This talk is part of the Institute of Astronomy Seminars series.

This talk is included in these lists:

• Cambridge Astronomy Talks
• Combined External Astrophysics Talks DAMTP
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• Cosmology, Astrophysics and General Relativity
• Institute of Astronomy Seminars
• Institute of Astronomy Talk Lists
• Kavli Institute for Cosmology Talk Lists
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• The Hoyle Lecture Theatre + Zoom

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