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arXiv 1604.08613astro-ph.GAastro-ph.SR
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化学演化模型中的流入、流出、产额和恒星星族混合

Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

Brett H. Andrews, David H. Weinberg, Ralph Schönrich, Jennifer A. Johnson

摘要:

化学演化模型是解释恒星丰度调查和理解星系演化的有力工具。然而,他们的预测在很大程度上取决于流入,流出,恒星形成效率(SFE),恒星初始质量函数,Ia型超新星延迟时间分布,恒星产量,和恒星星族混合的治疗。使用flexCE,一个灵活的单区化学演化代码,我们调查的影响和参数之间的权衡。两个关键参数是超临界流体和流出的质量负载参数,移动膝盖[O/Fe]-[Fe/H]和平衡的模拟渐近方法的丰度,分别。具有简单恒星形成历史的单区模型遵循[O/Fe]-[Fe/H]中的窄轨道,这与在该平面中观察到的双峰性(分离的高α和低α序列)不同。一个混合的一个区域模型与流入的时间尺度和流出的质量加载参数的变化,由内而外的星系形成的情况下,径向混合的动机,再现两个序列比一个区域模型有两个落入时代。我们提出了20种元素的[X/Fe]-[Fe/H]轨道,假设三种不同的超新星产额模型,并发现一些显着的差异与太阳附近的观测,特别是对元素与强烈的金属依赖性的产量。我们应用主成分丰度分析(PCAA)的模拟和现有的数据,以揭示丰度之间的主要相关性,并量化它们的贡献丰度空间的变化。对于恒星星族混合的情况下,α-元素和元素的丰度与金属依赖的产量分别占主导地位的第一和第二主成分,并共同解释99%的模型中的方差。flexCE是一个python包,可在https://github.com/bretthandrews/flexCE上获得。

英文摘要:

Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the stellar initial mass function, the Type Ia supernova delay time distribution, stellar yields, and stellar population mixing. Using flexCE, a flexible one-zone chemical evolution code, we investigate the effects of and trade-offs between parameters. Two critical parameters are SFE and the outflow mass-loading parameter, which shift the knee in [O/Fe]-[Fe/H] and the equilibrium abundances that the simulations asymptotically approach, respectively. One-zone models with simple star formation histories follow narrow tracks in [O/Fe]-[Fe/H] unlike the observed bimodality (separate high-alpha and low-alpha sequences) in this plane. A mix of one-zone models with inflow timescale and outflow mass-loading parameter variations, motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the two sequences better than a one-zone model with two infall epochs. We present [X/Fe]-[Fe/H] tracks for 20 elements assuming three different supernova yield models and find some significant discrepancies with solar neighborhood observations, especially for elements with strongly metallicity-dependent yields. We apply principal component abundance analysis (PCAA) to the simulations and existing data to reveal the main correlations amongst abundances and quantify their contributions to variation in abundance space. For the stellar population mixing scenario, the abundances of alpha-elements and elements with metallicity-dependent yields dominate the first and second principal components, respectively, and collectively explain 99% of the variance in the model. flexCE is a python package available at https://github.com/bretthandrews/flexCE.

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