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arXiv 2609.27048astro-ph.HEastro-ph.GA

厚盘中的原位恒星形成:Mrk 573金属增丰模型

In-Situ Star Formation in a Thick Disk: A Model for Metal Enrichment of Mrk 573

  • JILA, University of Colorado and National Institute of Standards and Technology(科罗拉多大学JILA研究所与美国国家标准与技术研究院)
  • Columbia Astrophysics Laboratory, Columbia University(哥伦比亚大学哥伦比亚天体物理实验室)
  • Department of Physics and Astronomy, Michigan State University(密歇根州立大学物理与天文系)
  • Center for Computational Astrophysics, Flatiron Institute(平顿研究所计算天体物理学中心)
  • Harvard-Smithsonian Center for Astrophysics(哈佛-史密森尼天体物理中心)
  • Astronomical Observatory of the Jagiellonian University(雅盖隆大学天文台)

机构由 AI 辅助整理,请以论文原文为准。

Hannalore J. Gerling-Dunsmore, Mitchell C. Begelman, Jared A. Goldberg, Taeho Ryu, Dominika Ł. Król

中文总结 AI 辅助

本文提出吸积盘原位恒星形成模型,解释Mrk 573星系核及双锥区域的金属增丰,发现厚盘模型与观测相符,薄盘模型被排除,并指出金属丰度可作为盘厚度的诊断指标。

中文摘要 AI 辅助

近期对邻近西弗特星系Mrk 573的观测发现,其星系核及环绕喷流的双锥区域显著富集金属。本文中,我们构建了一个简单的模型来解释观测到的金属增丰,假设在吸积盘中原位形成了一群质量在$10 - 30 \\, M_{\odot}$范围内的恒星。我们假设这些恒星按照萨尔皮特初始质量函数形成,并生成同质量场恒星预期的典型金属产量。我们发现,在厚盘($H/r \sim 0.1$)情形下,萨尔皮特恒星群可以轻易解释观测到的金属增丰,并为形成模型提供限制;同时,我们认为薄盘($H/r \lesssim 0.01$)与观测到的金属增丰不相容。在我们的模型中,活动星系核的金属丰度与盘厚度的关联最为显著,这暗示了一个潜在强有力的可观测诊断指标。

英文摘要

Recent observations of the nearby Seyfert galaxy Mrk 573 found that the galactic nucleus and bicone regions surrounding the jet are significantly metal-enriched. In this paper, we develop a simple model for the observed metal enrichment, assuming a population of stars in the $10 - 30 \, M_{\odot}$ range formed in-situ in the accretion disk. We assume the stars form according to a Salpeter initial mass function and generate the typical metal yields expected of field stars of the same mass. We find that in the thick disk ($H/r \sim 0.1$) case, a Salpeter population of stars can easily explain the observed metal enrichment and provide limits on the formation model; we also argue that a thin disk ($H/r \lesssim 0.01$) is incompatible with the observed metal enrichment. In our model, AGN metallicity scales most strongly with disk thickness, implying a potentially powerful observable diagnostic.

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