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Title: RESOLVE and ECO: Finding Low-metallicity z ∼ 0 Dwarf AGN Candidates Using Optimized Emission-line Diagnostics
Abstract Existing star-forming vs. active galactic nucleus (AGN) classification schemes using optical emission-line diagnostics mostly fail for low-metallicity and/or highly star-forming galaxies, missing AGN in typical z ∼ 0 dwarfs. To recover AGN in dwarfs with strong emission lines (SELs), we present a classification scheme optimizing the use of existing optical diagnostics. We use Sloan Digital Sky Survey emission-line catalogs overlapping the volume- and mass-limited REsolved Spectroscopy Of a Local VolumE (RESOLVE) and Environmental COntex (ECO) surveys to determine the AGN percentage in SEL dwarfs. Our photoionization grids show that the [O iii ]/H β versus [S ii ]/H α diagram (S ii plot) and [O iii ]/H β versus [O i ]/H α diagram (O i plot) are less metallicity sensitive and more successful in identifying dwarf AGN than the popular [O iii ]/H β versus [N ii ]/H α diagnostic (N ii plot or “BPT diagram”). We identify a new category of “star-forming AGN” (SF-AGN) classified as star-forming by the N ii plot but as AGN by the S ii and/or O i plots. Including SF-AGN, we find the z ∼ 0 AGN percentage in dwarfs with SELs to be ∼3%–16%, far exceeding most previous optical estimates (∼1%). The large range in our dwarf AGN percentage reflects differences in spectral fitting methodologies between catalogs. The highly complete nature of RESOLVE and ECO allows us to normalize strong emission-line galaxy statistics to the full galaxy population, reducing the dwarf AGN percentage to ∼0.6%–3.0%. The newly identified SF-AGN are mostly gas-rich dwarfs with halo mass <10 11.5 M ⊙ , where highly efficient cosmic gas accretion is expected. Almost all SF-AGN also have low metallicities ( Z ≲ 0.4 Z ⊙ ), demonstrating the advantage of our method.  more » « less
Award ID(s):
2007351
PAR ID:
10333820
Author(s) / Creator(s):
; ; ; ; ; ; ; ;
Date Published:
Journal Name:
The Astrophysical Journal
Volume:
931
Issue:
1
ISSN:
0004-637X
Page Range / eLocation ID:
44
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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