论文标题
检索HR 7672〜AB的C和O丰度:带有基准的棕色矮人的太阳能型主要恒星
Retrieving the C and O Abundances of HR 7672~AB: a Solar-Type Primary Star with a Benchmark Brown Dwarf
论文作者
论文摘要
基准棕色矮人(BD)是BD,其性能(例如质量和化学成分)精确,独立地测量。基准BDS在测试理论进化轨道,光谱合成和大气检索的基准BDS中很有价值。在这里,我们报告了合成光谱和基准BD的大气检索结果-HR 7672〜B-带有\ petit。首先,我们在带有太阳能组成的合成凤凰BT-SETTL光谱上测试检索框架。我们表明,检索到的c和o丰度与太阳值一致,但是检索到的c/o被高估了0.13-0.18,这是$ \ sim $ \ sim $ \ sim $ 4倍$ 4倍。其次,我们使用Keck Planet Imager和Tarricer(KPIC)和近红外光度法的高光谱分辨率数据(r = 35,000)对HR 7672〜B进行检索。我们检索[C/H],[O/H]和C/O为$ -0.24 \ PM0.05 $,$ -0.19 \ PM0.04 $,$ 0.52 \ pm0.02 $。这些值与1.5- $σ$内的HR 7672〜a的值一致。因此,HR 7672〜b仅是几个基准BD(以及GL 570〜D和HD 3651〜B),这些BDS已被证明与主要恒星具有一致的元素丰度。我们的工作提供了测试和执行大气检索的实用程序,并阐明了使用高分辨率数据和低分辨率数据的潜在系统学系统。
A benchmark brown dwarf (BD) is a BD whose properties (e.g., mass and chemical composition) are precisely and independently measured. Benchmark BDs are valuable in testing theoretical evolutionary tracks, spectral synthesis, and atmospheric retrievals for sub-stellar objects. Here, we report results of atmospheric retrieval on a synthetic spectrum and a benchmark BD -- HR 7672~B -- with \petit. First, we test the retrieval framework on a synthetic PHOENIX BT-Settl spectrum with a solar composition. We show that the retrieved C and O abundances are consistent with solar values, but the retrieved C/O is overestimated by 0.13-0.18, which is $\sim$4 times higher than the formal error bar. Second, we perform retrieval on HR 7672~B using high spectral resolution data (R=35,000) from the Keck Planet Imager and Characterizer (KPIC) and near infrared photometry. We retrieve [C/H], [O/H], and C/O to be $-0.24\pm0.05$, $-0.19\pm0.04$, and $0.52\pm0.02$. These values are consistent with those of HR 7672~A within 1.5-$σ$. As such, HR 7672~B is among only a few benchmark BDs (along with Gl 570~D and HD 3651~B) that have been demonstrated to have consistent elemental abundances with their primary stars. Our work provides a practical procedure of testing and performing atmospheric retrieval, and sheds light on potential systematics of future retrievals using high- and low-resolution data.