Revealing AGNs Through TESS Variability

TL;DR

This study leverages TESS optical variability data to identify 29 candidate AGNs, including low-mass galaxy hosts, demonstrating a new method that can uncover previously undetected AGNs and estimate black hole masses.

Contribution

The paper introduces a novel variability-based approach using TESS data to identify AGNs, especially in low-mass galaxies, expanding the detection capabilities beyond traditional methods.

Findings

Identified 29 candidate AGNs via TESS variability.

18 candidates match known AGNs or other diagnostics.

Estimated discovery of ~45 more AGNs in the full TESS dataset.

Abstract

We used Transiting Exoplanet Survey Satellite (TESS) data to identify 29 candidate active galactic nuclei (AGNs) through their optical variability. The high-cadence, high-precision TESS light curves present a unique opportunity for the identification of AGNs, including those not selected through other methods. Of the candidates, we found that 18 have either previously been identified as AGNs in the literature or could have been selected based on emission-line diagnostics, mid-IR colors, or X-ray luminosity. AGNs in low-mass galaxies offer a window into supermassive black hole (SMBH) and galaxy co-evolution and 8 of the 29 candidates have estimated black hole masses $\mathrm{\lesssim 10^{6} M_{\odot}}$. The low-mass galaxies NGC 4395 and NGC 4449 are two of our five "high-confidence" candidates. By applying our methodology to the entire TESS main and extended mission datasets, we expect to identify $\sim$45 more AGN candidates, of which $\sim$26 will be new and $\sim$8 will be in low-mass galaxies.