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Universty of the Western Cape

Detecting anomalous transients in meertrap data

Abstract

dc:description.abstract

In an era distinguished by significant technological progress, the prevalence of large and complex datasets characterizes the "big data" era across various disciplines. With improved telescopes being built aimed at generating datasets of unprecedented volumes, there is incredible potential for discovery. The MeerKAT radio telescope in South Africa has proven to be an excellent telescope to search for fast radio transients such as pulsars and fast radio bursts (FRBs). MeerTRAP (more TRAnsients and Pulsars), which commensally uses MeerKAT to search for fast radio transients, detects tens of thousands of candidate objects daily (on average), although the vast majority are not of astrophysical origin. Automated techniques such as machine learning are routinely used to identify targeted astrophysical transients. However, an emerging application of machine learning is to aid the detection of unidentified or rare sources, referred to as anomalies.

Degree

thesis:*
Grantor dc:publisher.institution
Universty of the Western Cape
Year dc:date.issued
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Petersen-Charles, Jade Lindsay

Subjects

dc:subject × 5

Rights

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Chain of custody

source
Harvested from
University of the Western Cape
Base URL
uwcscholar.uwc.ac.za:8443/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Petersen-Charles, Jade Lindsay. Detecting anomalous transients in meertrap data. Universty of the Western Cape, 2024.