Bayesian inference of T Tauri star properties using multi-wavelength survey photometry
Bayesian inference of T Tauri star properties using multi-wavelength survey photometry
复制标题
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
中科院分区:
文献类型:
--
作者:
Barentsen G
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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2000
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作者:
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2008
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影响因子:
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DOI:
10.1111/j.1745-3933.2006.00177.x
发表时间:
2006
影响因子:
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作者:
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