Spectroscopic Confirmation of Obscured AGN Populations from Unsupervised Machine Learning

Spectroscopic Confirmation of Obscured AGN Populations from Unsupervised Machine Learning

We present the result of a spectroscopic campaign targeting active galactic nucleus (AGN) candidates selected using a novel unsupervised machine-learning (ML) algorithm trained on optical and mid-infrared photometry. AGN candidates are chosen without incorporating prior AGN selection criteria and ar...

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Bibliographic Details
Main Authors: Raphael E. Hviding, Kevin N. Hainline, Andy D. Goulding, Jenny E. Greene
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:The Astronomical Journal
Subjects:
Active galactic nuclei
Dimensionality reduction
Galaxy spectroscopy
Online Access:https://doi.org/10.3847/1538-3881/ad28b4

Internet

https://doi.org/10.3847/1538-3881/ad28b4

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