Valentina Tardugno Poleo
Identifying Active Galactic Nuclei at z ∼ 3 from the HETDEX Survey Using Machine Learning
Tardugno Poleo, Valentina; Finkelstein, Steven L.; Leung, Gene; Mentuch Cooper, Erin; Gebhardt, Karl; Farrow, Daniel J.; Gawiser, Eric; Zeimann, Greg; Schneider, Donald P.; Morabito, Leah; Mock, Daniel; Liu, Chenxu
Authors
Steven L. Finkelstein
Gene Leung
Erin Mentuch Cooper
Karl Gebhardt
Dr Daniel Farrow D.J.Farrow@hull.ac.uk
Lecturer and Director of Education
Eric Gawiser
Greg Zeimann
Donald P. Schneider
Leah Morabito
Daniel Mock
Chenxu Liu
Abstract
We used data from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) to study the incidence of AGN in continuum-selected galaxies at z ∼ 3. From optical and infrared imaging in the 24 deg2 Spitzer HETDEX Exploratory Large Area survey, we constructed a sample of photometric-redshift selected z ∼ 3 galaxies. We extracted HETDEX spectra at the position of 716 of these sources and used machine-learning methods to identify those which exhibited AGN-like features. The dimensionality of the spectra was reduced using an autoencoder, and the latent space was visualized through t-distributed stochastic neighbor embedding. Gaussian mixture models were employed to cluster the encoded data and a labeled data set was used to label each cluster as either AGN, stars, high-redshift galaxies, or low-redshift galaxies. Our photometric redshift (photoz) sample was labeled with an estimated 92% overall accuracy, an AGN accuracy of 83%, and an AGN contamination of 5%. The number of identified AGN was used to measure an AGN fraction for different magnitude bins. The ultraviolet (UV) absolute magnitude where the AGN fraction reaches 50% is M UV = −23.8. When combined with results in the literature, our measurements of AGN fraction imply that the bright end of the galaxy luminosity function exhibits a power law rather than exponential decline, with a relatively shallow faint-end slope for the z ∼ 3 AGN luminosity function.
Citation
Tardugno Poleo, V., Finkelstein, S. L., Leung, G., Mentuch Cooper, E., Gebhardt, K., Farrow, D. J., Gawiser, E., Zeimann, G., Schneider, D. P., Morabito, L., Mock, D., & Liu, C. (2023). Identifying Active Galactic Nuclei at z ∼ 3 from the HETDEX Survey Using Machine Learning. Astronomical Journal, 165(4), Article 153. https://doi.org/10.3847/1538-3881/acba92
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 7, 2023 |
Online Publication Date | Mar 10, 2023 |
Publication Date | Apr 1, 2023 |
Deposit Date | Apr 17, 2024 |
Publicly Available Date | Apr 23, 2024 |
Journal | Astronomical Journal |
Print ISSN | 0004-6256 |
Publisher | American Astronomical Society |
Peer Reviewed | Peer Reviewed |
Volume | 165 |
Issue | 4 |
Article Number | 153 |
DOI | https://doi.org/10.3847/1538-3881/acba92 |
Public URL | https://hull-repository.worktribe.com/output/4626508 |
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Copyright Statement
© 2023. The Author(s). Published by the American Astronomical Society.
Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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