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Ivy Wong
re-joined CASS last year, as a CSIRO Science Leader
working on the big data challenges in the SKA era.
Her most recent co-authored publication was led by her
co-supervised PhD student, Matthew Alger (ANU), who developed an
interpretable machine learning-based classifier of Faraday complexity.
The image above shows 142 Faraday spectra (also known
as Faraday dispersion functions) from ATCA observations
(Livingston et al. 2021)
that have been ordered in order of Faraday complexity from
very simple (top) to complex (bottom). The numbers are logistic
regression probabilities that the Faraday spectrum is complex. This is
the first application of machine learning to observed Faraday spectra,
as previous studies were based on simulated spectra
(e.g., Brown et al. 2019).
Check out
Alger et al. 2021 for more details.
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