论文标题

莲花:一种(非)LTE优化工具,用于均匀推导出色的大气参数

LOTUS: A (non-)LTE Optimization Tool for Uniform derivation of Stellar atmospheric parameters

论文作者

Li, Yangyang, Ezzeddine, Rana

论文摘要

精确的基本大气恒星参数和恒星中各个元素的丰度确定对于所有恒星种群研究都很重要。但是,非本地热力学平衡(非LTE;以下NLTE)模型通常对于如此高精度而言很重要,但是,计算上很复杂且昂贵,这使得在光谱分析中使用的模型较少。为了减轻此类模型的计算负担,我们开发了一种健壮的1D,LTE和NLTE基本大气恒星参数推导工具,$ \ texttt {Lotus} $,以确定有效温度$ t _ {\ satry $ \ log g $,$ \ log g $,METALLIC $ \ \ \ \ \ \ fe/hhs $ and imm y Mathrm {eff}} $速度$ v _ {\ mathrm {Mic}} $用于FGK类型星星,从相同的宽度(EW)测量Fe I和Fe II线。我们利用一般的增长方法曲线来考虑相应大气恒星参数上每条Fe I和Fe II线的EW依赖性。然后,使用全局微分进化优化算法来得出优化的基本参数。此外,$ \ texttt {lotus} $可以使用马尔可夫链蒙特卡洛(MCMC)算法来确定每个恒星参数的精确不确定性。我们在基准恒星的样本中测试并应用$ \ texttt {lotus} $,以及带有K2调查的可用星号表面重力的恒星,以及$ r $ - 过程联盟(RPA)调查的金属贫困星。我们发现,在$ \ texttt {lotus} $中,我们的NLTE衍生参数之间的一致性非常好。我们提供代码的公开访问以及GitHub上可用的预计NLTE EW网格的开放式访问,并提供有关ReadThedocs的工作示例的文档。

Precise fundamental atmospheric stellar parameters and abundance determination of individual elements in stars are important for all stellar population studies. Non-Local Thermodynamic Equilibrium (Non-LTE; hereafter NLTE) models are often important for such high precision, however, can be computationally complex and expensive, which renders the models less utilized in spectroscopic analyses. To alleviate the computational burden of such models, we developed a robust 1D, LTE and NLTE fundamental atmospheric stellar parameter derivation tool, $\texttt{LOTUS}$, to determine the effective temperature $T_{\mathrm{eff}}$, surface gravity $\log g$, metallicity $\mbox{[Fe/H]}$ and microturbulent velocity $v_{\mathrm{mic}}$ for FGK type stars, from equivalent width (EW) measurements of Fe I and Fe II lines. We utilize a generalized curve of growth method to take into account the EW dependencies of each Fe I and Fe II line on the corresponding atmospheric stellar parameters. A global differential evolution optimization algorithm is then used to derive the optimized fundamental parameters. Additionally, $\texttt{LOTUS}$ can determine precise uncertainties for each stellar parameter using a Markov Chain Monte Carlo (MCMC) algorithm. We test and apply $\texttt{LOTUS}$ on a sample of benchmark stars, as well as stars with available asteroseismic surface gravities from the K2 survey, and metal-poor stars from $R$-process Alliance (RPA) survey. We find very good agreement between our NLTE-derived parameters in $\texttt{LOTUS}$ to non-spectroscopic values within $T_{\mathrm{eff}}=\pm 30$ K and $\log g=\pm 0.10$ dex for benchmark stars. We provide open access of our code, as well as of the interpolated pre-computed NLTE EW grids available on Github, and documentation with working examples on Readthedocs.

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