Bayesian inference of T Tauri star properties using multi-wavelength survey photometry

Bayesian inference of T Tauri star properties using multi-wavelength survey photometry
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使用多波长勘测光度法对 Tauri T 星特性进行贝叶斯推断

DOI:
10.1093/mnras/sts462
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发表时间:
2013
影响因子:
4.8
通讯作者:
Barentsen G
Barentsen G
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
Barentsen G

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在星星和行星的形成领域有许多相关的公开问题。我们需要大量的恒星形成区年轻恒星的统计样本来触发我们理解的突破,但是大多数光学研究都是基于各种各样的光谱仪和分析方法,这引入了很大的偏差。在这里,我们展示了如何使用图形贝叶斯网络来构建一个分层概率模型,该模型允许主序前的年龄,质量,吸积率和吸积率将使用两个广泛可用的光度测量数据库(艾萨克·牛顿望远镜光度测量Hα Surveyr′/Hα/i′和两微米全天测量J波段星等)进行估算。由于我们的方法不依赖于光谱,它可以很容易地应用于均匀地研究大量的集群,Gaia将产生成员名单。我们解释了如何使用马尔可夫链蒙特卡罗方法进行分析,并提供了源代码。然后,我们展示了它在恒星形成区NGC 2264的587个已知低质量成员上的使用(锥状星云),达到3.0万年的年龄中位数,吸积分数为20 ± 2%,吸积率中位数为10− 8.4兆年− 1。在这项工作中制定的贝叶斯分析提供的结果与光谱研究已经在文献中,但是通过仅依赖于光度测定而以很高的效率实现这一点。这是从以前的光度学研究向前迈出的重要一步,因为概率方法确保了干扰参数,如消光和距离,完全包括在分析中,对任何退化都有清晰的了解。
There are many pertinent open issues in the area of star and planet formation. Large statistical samples of young stars across star-forming regions are needed to trigger a breakthrough in our understanding, but most optical studies are based on a wide variety of spectrographs and analysis methods, which introduces large biases.Here we show how graphical Bayesian networks can be employed to construct a hierarchical probabilistic model which allows pre-main-sequence ages, masses, accretion rates and extinctions to be estimated using two widely available photometric survey data bases (Isaac Newton Telescope Photometric Hα Surveyr′/Hα/i′and Two Micron All Sky SurveyJ-band magnitudes). Because our approach does not rely on spectroscopy, it can easily be applied to ho‐mogeneously study the large number of clusters for whichGaiawill yield membership lists.We explain how the analysis is carried out using the Markov chain Monte Carlo method and providepythonsource code. We then demonstrate its use on 587 known low-mass members of the star-forming region NGC 2264 (Cone Nebula), arriving at a median age of 3.0 Myr, an accretion fraction of 20 ± 2 per cent and a median accretion rate of 10−8.4M⊙yr−1.The Bayesian analysis formulated in this work delivers results which are in agreement with spectroscopic studies already in the literature, but achieves this with great efficiency by depending only on photometry. It is a significant step forward from previous photometric studies because the probabilistic approach ensures that nuisance parameters, such as extinction and distance, are fully included in the analysis with a clear picture on any degeneracies.
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