Anomaly Detection and Radio-frequency Interference Classification with Unsupervised Learning in Narrowband Radio Technosignature Searches

Anomaly Detection and Radio-frequency Interference Classification with Unsupervised Learning in Narrowband Radio Technosignature Searches

The search for radio technosignatures is an anomaly detection problem: Candidate signals represent needles of interest in the proverbial haystack of radio-frequency interference (RFI). Current search frameworks find an enormity of false-positive signals, especially in large surveys, requiring manual...

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Bibliographic Details
Main Authors: Ben Jacobson-Bell, Steve Croft, Carmen Choza, Alex Andersson, Daniel Bautista, Vishal Gajjar, Matthew Lebofsky, David H. E. MacMahon, Caleb Painter, Andrew P. V. Siemion
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astronomical Journal
Subjects:
Outlier detection
Clustering
Technosignatures
Search for extraterrestrial intelligence
Radio astronomy
Online Access:https://doi.org/10.3847/1538-3881/adb8e7

Internet

https://doi.org/10.3847/1538-3881/adb8e7

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