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Poster
in
Workshop: Machine Learning and the Physical Sciences

A Granular Method for Finding Anomalous Light Curves and their Analogs

Kushal Tirumala


Abstract:

Anomalous light curves indicate rare and as yet unexplainable phenomena associated with astronomical sources. With existing large surveys like the Zwicky Transient Facility (ZTF), and upcoming ones such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) that will observe astrophysical transients at all time scales and produce archival light curves in the billions, there is an immediate need for methods that reveal anomalous light curves. Previous work explores anomalous light curve detection, but little work has gone into finding analogs of such light curves. That is, given a light curve of interest, can we find other examples in the dataset that behave similarly? We present such a pipeline that (1) identifies anomalous light curves, and (2) finds additional examples of specific rare classes, in a large corpora of light curves. We apply this method to Kepler data, finding around 5000 previously unknown anomalies, and present a subset of these anomalies along with their potential astrophysical classification.

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