LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
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DOI：
10.3847/1538-3881/acb7f0
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发表时间：
2022-07
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影响因子：
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通讯作者：
Yangyang 扬洋 Li 李;R. Ezzeddine
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作者：
Yangyang 扬洋 Li 李;R. Ezzeddine
精确的基本恒星大气参数和恒星中单个元素的丰度测定对所有恒星族研究都是重要的。非局部热力学平衡（Non-local thermodynamics equilibrium, non-LTE，以下简称NLTE）模型对于这样的高精度通常是很重要的，然而，计算复杂且昂贵，这使得这些模型在光谱分析中很少被利用。为了减轻这些模型的计算负担，我们开发了一个强大的1D， NLTE基本大气恒星参数推导工具LOTUS，通过等效宽度（EW）测量Fe i和Fe ii线来确定fgk型恒星的有效温度T eff，表面重力测井，金属丰度[Fe/H]和微湍流速度v mic。我们利用一种广义的生长曲线方法来考虑每条Fe i和Fe ii线对相应大气恒星参数的EW依赖性。然后采用全局差分进化优化算法推导基本参数。此外，LOTUS可以使用马尔可夫链蒙特卡罗算法确定每个恒星参数的精确不确定性。我们在基准恒星样本上测试和应用LOTUS，以及K2调查中具有可用星地震表面重力的恒星，以及Gaia-ESO和R-Process联盟调查中金属贫乏的恒星。我们发现，我们在LOTUS中得到的nlte参数与非光谱值之间的一致性非常好，平均在T =±30 K范围内，基准恒星的log =±0.10指数。我们提供了我们的代码的开放访问，以及在Github上可用的插值预计算的NLTE EW网格（该软件在MIT许可下可在Github 33 https://github.com/Li-Yangyang/LOTUS上获得，版本0.1.1（作为持久版本）存档在Zenodo）和Readthedocs书中的工作示例文档。https://github.com/Li-Yangyang/LOTUS
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, NLTE fundamental atmospheric stellar parameter derivation tool, LOTUS, to determine the effective temperature T eff, surface gravity logg , metallicity [Fe/H], and microturbulent velocity v 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 fundamental parameters. Additionally, LOTUS can determine precise uncertainties for each stellar parameter using a Markov Chain Monte Carlo algorithm. We test and apply 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 the Gaia-ESO and R-Process Alliance surveys. We find very good agreement between our NLTE-derived parameters in LOTUS to nonspectroscopic values on average within T eff = ±30 K, and logg = ±0.10 dex for benchmark stars. We provide open access of our code, as well as of the interpolated precomputed NLTE EW grids available on Github (the software is available on GitHub 3 3 https://github.com/Li-Yangyang/LOTUS under an MIT License, and version 0.1.1 (as the persistent version) is archived in Zenodo) and documentation with working examples on the Readthedocs book. https://github.com/Li-Yangyang/LOTUS