SDSS-IV MaNGA: Refining Strong Line Diagnostic Classifications Using Spatially Resolved Gas Dynamics
SDSS-IV MaNGA: Refining Strong Line Diagnostic Classifications Using Spatially Resolved Gas Dynamics
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DOI：
10.3847/1538-4357/abfe0a
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发表时间：
2020-11
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通讯作者：
D. Law;Xihan Ji;F. Belfiore;M. Bershady;M. Cappellari;K. Westfall;R. Yan;D. Bizyaev;J. Brownstein-J.-Br
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作者：
D. Law;Xihan Ji;F. Belfiore;M. Bershady;M. Cappellari;K. Westfall;R. Yan;D. Bizyaev;J. Brownstein-J.-Br
我们使用MaNGA积分场光谱星系调查的统计能力来改进用于分类星系中气体电离特性的强线诊断边界的定义。我们探测到分布在7400个不同恒星质量、恒星形成速率和形态类型的单个星系中的360万spaxel的线发射，发现气相速度色散σ Hα与传统的光学发射在线比（如[S ii]/Hα、[N ii]/Hα、[O i]/Hα和[O iii]/Hβ）密切相关。线比与星系H区电离最一致的Spaxels，其动态冷视距速度分布（losvd）范围窄，峰值约为25 km s−1，对应于星系薄盘，而与活动星系核（agn）和低电离发射线区（LI(N)ERs）相一致的Spaxels，其losvd范围明显更宽，延伸至200 km s−1。恒星形成区、AGN区和LI(N)ER区在恒星速度色散、恒星群年龄、Hα等效宽度和给定星系内的典型半径方面也彼此分离得很好。我们使用我们的观察来修改传统的发射在线诊断分类，以便它们在诊断线比率空间的二维表示和考虑恒星形成模型表面复杂折叠的多维空间中可靠地识别不同的动态样本。通过将MaNGA观测结果与SDSS单纤维星系样本进行比较，我们注意到后者系统地偏向于位于3″纤维足迹之外的年轻，低金属丰度的恒星形成区域。
We use the statistical power of the MaNGA integral-field spectroscopic galaxy survey to improve the definition of strong line diagnostic boundaries used to classify gas ionization properties in galaxies. We detect line emission from 3.6 million spaxels distributed across 7400 individual galaxies spanning a wide range of stellar masses, star formation rates, and morphological types, and find that the gas-phase velocity dispersion σ Hα correlates strongly with traditional optical emission-line ratios such as [S ii]/Hα, [N ii]/Hα, [O i]/Hα, and [O iii]/Hβ. Spaxels whose line ratios are most consistent with ionization by galactic H ii regions exhibit a narrow range of dynamically cold line-of-sight velocity distributions (LOSVDs) peaked around 25 km s−1 corresponding to a galactic thin disk, while those consistent with ionization by active galactic nuclei (AGNs) and low-ionization emission-line regions (LI(N)ERs) have significantly broader LOSVDs extending to 200 km s−1. Star-forming, AGN, and LI(N)ER regions are additionally well separated from each other in terms of their stellar velocity dispersion, stellar population age, Hα equivalent width, and typical radius within a given galaxy. We use our observations to revise the traditional emission-line diagnostic classifications so that they reliably identify distinct dynamical samples both in two-dimensional representations of the diagnostic line ratio space and in a multidimensional space that accounts for the complex folding of the star-forming model surface. By comparing the MaNGA observations to the SDSS single-fiber galaxy sample, we note that the latter is systematically biased against young, low-metallicity star-forming regions that lie outside of the 3″ fiber footprint.