Application of anomaly detection techniques to astrophysical transients

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Date

2021

Journal Title

Journal ISSN

Volume Title

Publisher

University of Western Cape

Abstract

We are fast moving into an era where data will be the primary driving factor for discovering new unknown astronomical objects and also improving our understanding of the current rare astronomical objects. Wide field survey telescopes such as the Square Kilometer Array (SKA) and Vera C. Rubin observatory will be producing enormous amounts of data over short timescales. The Rubin observatory is expected to record ∼ 15 terabytes of data every night during its ten-year Legacy Survey of Space and Time (LSST), while the SKA will collect ∼100 petabytes of data per day. Fast, automated, and datadriven techniques, such as machine learning, are required to search for anomalies in these enormous datasets, as traditional techniques such as manual inspection will take months to fully exploit such datasets.

Description

>Magister Scientiae - MSc

Keywords

Astronomy, Data, Square Kilometer Array (SKA), Rubin observatory, Anomaly detection

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