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
Daniel J. Farrow
Eric Gawiser
Greg Zeimann
Donald P. Schneider
Professor Leah Morabito leah.k.morabito@durham.ac.uk
Professor
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 MUV = −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., …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 | May 30, 2023 |
Publicly Available Date | May 30, 2023 |
Journal | The Astronomical Journal |
Print ISSN | 0004-6256 |
Electronic ISSN | 1538-3881 |
Publisher | IOP Publishing |
Peer Reviewed | Peer Reviewed |
Volume | 165 |
Issue | 4 |
Article Number | 153 |
DOI | https://doi.org/10.3847/1538-3881/acba92 |
Public URL | https://durham-repository.worktribe.com/output/1173213 |
Files
Published Journal Article
(939 Kb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
Copyright Statement
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.
You might also like
LOFAR HBA observations of the Euclid Deep Field North (EDFN)
(2024)
Journal Article
Cosmic evolution of FRI and FRII sources out to z = 2.5
(2024)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search