Identifying Active Galactic Nuclei at z ∼ 3 from the HETDEX Survey Using Machine Learning

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 deg 2 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 (photo z ) 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.