A post-merger enhancement only in star-forming Type 2 Seyfert galaxies: the deep learning view

Avirett-Mackenzie, M. S.; Villforth, C.; Huertas-Company, M.; Wuyts, S.; Alexander, D. M.; Bonoli, S.; Lapi, A.; Lopez, I. E.; Ramos Almeida, C.; Shankar, F.

doi:10.1093/mnras/stae183

A post-merger enhancement only in star-forming Type 2 Seyfert galaxies: the deep learning view

Journal Article · Thu Feb 22 00:00:00 EST 2024 · Monthly Notices of the Royal Astronomical Society

DOI:https://doi.org/10.1093/mnras/stae183· OSTI ID:2310995

Avirett-Mackenzie, M. S.; ; ; ; Alexander, D. M.; Bonoli, S.; ; ; ;

ABSTRACT

Supermassive black holes require a reservoir of cold gas at the centre of their host galaxy in order to accrete and shine as active galactic nuclei (AGN). Major mergers have the ability to drive gas rapidly inwards, but observations trying to link mergers with AGN have found mixed results due to the difficulty of consistently identifying galaxy mergers in surveys. This study applies deep learning to this problem, using convolutional neural networks trained to identify simulated post-merger galaxies from survey-realistic imaging. This provides a fast and repeatable alternative to human visual inspection. Using this tool, we examine a sample of ∼8500 Seyfert 2 galaxies ($$L[\mathrm{O\, {\small III}}] \sim 10^{38.5 - 42}$$ erg s−1) at z < 0.3 in the Sloan Digital Sky Survey and find a merger fraction of $$2.19_{-0.17}^{+0.21}$$ per cent compared with inactive control galaxies, in which we find a merger fraction of $$2.96_{-0.20}^{+0.26}$$ per cent, indicating an overall lack of mergers among AGN hosts compared with controls. However, matching the controls to the AGN hosts in stellar mass and star formation rate reveals that AGN hosts in the star-forming blue cloud exhibit a ∼2 × merger enhancement over controls, while those in the quiescent red sequence have significantly lower relative merger fractions, leading to the observed overall deficit due to the differing M*–SFR distributions. We conclude that while mergers are not the dominant trigger of all low-luminosity, obscured AGN activity in the nearby Universe, they are more important to AGN fuelling in galaxies with higher cold gas mass fractions as traced through star formation.

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Sponsoring Organization:: USDOE

OSTI ID:: 2310995

Journal Information:: Monthly Notices of the Royal Astronomical Society, Journal Name: Monthly Notices of the Royal Astronomical Society Journal Issue: 4 Vol. 528; ISSN 0035-8711

Publisher:: Oxford University PressCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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DO THE MOST MASSIVE BLACK HOLES AT z = 2 GROW VIA MAJOR MERGERS? Mechtley, M.; Jahnke, K.; Windhorst, R. A. The Astrophysical Journal, Vol. 830, Issue 2 https://doi.org/10.3847/0004-637X/830/2/156	journal	October 2016
The Astropy Project: Building an Open-science Project and Status of the v2.0 Core Package Price-Whelan, A. M.; Sipőcz, B. M.; Günther, H. M. The Astronomical Journal, Vol. 156, Issue 3 https://doi.org/10.3847/1538-3881/aabc4f	journal	August 2018
Evidence for Merger-driven Growth in Luminous, High- z , Obscured AGNs in the CANDELS/COSMOS Field Donley, J. L.; Kartaltepe, J.; Kocevski, D. The Astrophysical Journal, Vol. 853, Issue 1 https://doi.org/10.3847/1538-4357/aa9ffa	journal	January 2018
The Dramatic Size and Kinematic Evolution of Massive Early-type Galaxies Lapi, A.; Pantoni, L.; Zanisi, L. The Astrophysical Journal, Vol. 857, Issue 1 https://doi.org/10.3847/1538-4357/aab6af	journal	April 2018
LSST: From Science Drivers to Reference Design and Anticipated Data Products Ivezić, Željko; Kahn, Steven M.; Tyson, J. Anthony The Astrophysical Journal, Vol. 873, Issue 2 https://doi.org/10.3847/1538-4357/ab042c	journal	March 2019
Major Mergers Are Not the Dominant Trigger for High-accretion AGNs at z ∼ 2 Marian, Victor; Jahnke, Knud; Mechtley, Mira The Astrophysical Journal, Vol. 882, Issue 2 https://doi.org/10.3847/1538-4357/ab385b	journal	September 2019
A Significant Excess in Major Merger Rate for AGNs with the Highest Eddington Ratios at z < 0.2 Marian, Victor; Jahnke, Knud; Andika, Irham The Astrophysical Journal, Vol. 904, Issue 1 https://doi.org/10.3847/1538-4357/abbd3e	journal	November 2020
Cosmological Simulations of Quasar Fueling to Subparsec Scales Using Lagrangian Hyper-refinement Anglés-Alcázar, Daniel; Quataert, Eliot; Hopkins, Philip F. The Astrophysical Journal, Vol. 917, Issue 2 https://doi.org/10.3847/1538-4357/ac09e8	journal	August 2021
The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package* No authors listed The Astrophysical Journal, Vol. 935, Issue 2 https://doi.org/10.3847/1538-4357/ac7c74	journal	August 2022
Identifying Galaxy Mergers in Simulated CEERS NIRCam Images Using Random Forests Rose, Caitlin; Kartaltepe, Jeyhan S.; Snyder, Gregory F. The Astrophysical Journal, Vol. 942, Issue 1 https://doi.org/10.3847/1538-4357/ac9f10	journal	January 2023
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Adam: A Method for Stochastic Optimization Kingma, Diederik P.; Ba, Jimmy arXiv https://doi.org/10.48550/arXiv.1412.6980	preprint	January 2014
Identifying Mergers Using Quantitative Morphologies in Zoom Simulations of High-Redshift Galaxies Abruzzo, Matthew W.; Narayanan, Desika; Davé, Romeel arXiv https://doi.org/10.48550/arXiv.1803.02374	preprint	January 2018
The Connection between Mergers and AGN Activity in Simulated and Observed Massive Galaxies Sharma, Ray S.; Choi, Ena; Somerville, Rachel S. arXiv https://doi.org/10.48550/arXiv.2101.01729	text	January 2021
A Deep Learning Approach for Characterizing Major Galaxy Mergers Koppula, Skanda; Bapst, Victor; Huertas-Company, Marc arXiv https://doi.org/10.48550/arXiv.2102.05182	preprint	January 2021
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