论文标题

$ h $ - 带温度和酷巨人的金属指标:贝叶斯框架中的经验关系

$H$-band Temperature and Metallicity Indicators for Cool Giants: Empirical Relations in Bayesian Framework

论文作者

Ghosh, Supriyo, Ninan, J. P., Ojha, D. K.

论文摘要

我们在这里探索了近红外的$ H $频带大气窗口,目的是提供定量的诊断工具,以推导出色的参数,例如有效温度($ t_ {eff} $)和金属性([$ fe/h h $]),酷巨人($ t_ {eff} $ $ <$ 5000 k),使用低位分析图像。我们从X-Shooter Spectral库中获得了177个很酷的巨头,涵盖了更宽的金属范围($ -2.35 dex $ <$ <$ <$ <$ fe/h $ <$ <$ 0.5 dex)。将光谱分辨率降低到r $ \ sim $ 1200,我们估计了几个重要光谱特征的等效宽度,并研究了具有恒星参数的光谱特征的行为。同样,在贝叶斯框架中建立了用于得出$ t_ {eff} $和[$ fe/h $]的经验关系。我们发现,$^{12} $ CO at 1.56 $ $ m和1.62 $μ$ m,$^{12} $ co+mgi at 1.71 $ $ m是最好的三$ t_ {fef} $指示剂,其典型精度分别为153 k,123 k,123 k和107 k。立方贝叶斯模型提供了最佳的金属估计器,其典型精度为0.22 dex,0.28 dex和0.24 dex的FEH为1.62 $ $ $ m,$^{12} $ CO,分别为1.64 $μ$ m,而Fe i $ m,分别为1.66 $ m $ m。 We also showed a detailed quantitative metallicity dependence of $T_{eff}-$EWs correlations defining three metallicity groups, supersolar ([$Fe/H$] $>$ 0.0 dex), solar ($-$0.3 dex $<$ [$Fe/H$] $<$ 0.3 dex), and subsolar ([$Fe/H$] $<$ $-$0.3 dex), from Hierarchical贝叶斯建模。太阳能关系和生物关系之间的差异在统计上是显着的,但是太阳能和超极基之间的这种差异并不明显。

We explored here the near-infrared $H$-band atmospheric window aiming to provide quantitative diagnostic tools for deriving stellar parameters, for instance, effective temperature ($T_{eff}$) and metallicity ([$Fe/H$]), of cool giants ($T_{eff}$ $<$ 5000 K) using low-resolution spectra. We obtained 177 cool giants from the X-shooter spectral library covering a wider metallicity range ($-$2.35 dex $<$ [$Fe/H$] $<$ 0.5 dex) than in earlier works. Degrading the spectral resolution to R$\sim$ 1200, we estimated equivalent widths of several important spectral features, and the behavior of spectral features with stellar parameters are studied. Also, the empirical relations for deriving $T_{eff}$ and [$Fe/H$] are established in the Bayesian framework. We found that $^{12}$CO at 1.56 $μ$m and 1.62 $μ$m, and $^{12}$CO+MgI at 1.71 $μ$m are the best three $T_{eff}$ indicators with a typical accuracy of 153 K, 123 K and 107 K, respectively. The cubic Bayesian model provides the best metallicity estimator with a typical accuracy of 0.22 dex, 0.28 dex, and 0.24 dex for FeH at 1.62 $μ$m, $^{12}$CO at 1.64 $μ$m, and Fe I at 1.66 $μ$m, respectively. We also showed a detailed quantitative metallicity dependence of $T_{eff}-$EWs correlations defining three metallicity groups, supersolar ([$Fe/H$] $>$ 0.0 dex), solar ($-$0.3 dex $<$ [$Fe/H$] $<$ 0.3 dex), and subsolar ([$Fe/H$] $<$ $-$0.3 dex), from Hierarchical Bayesian modelling. The difference between the solar and subsolar relationship is statistically significant, but such difference is not evident between the solar and supersolar groups.

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