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Toward Detection of Exoplanetary Rings via Transit Photometry: Methodology and a Possible Candidate

机译:通过运输光度法探测系外环的方法和可能的候选方法

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摘要

The detection of a planetary ring of exoplanets remains one of the most attractive, but challenging, goals in the field of exoplanetary science. We present a methodology that implements a?systematic search for exoplanetary rings via transit photometry of long-period planets. This?methodology relies on a precise integration scheme that?we develop to compute a transit light curve of a ringed planet. We apply the methodology to 89 long-period planet candidates from the Kepler data so as to estimate, and/or set upper limits on, the parameters of possible rings. While the?majority of our samples do not have sufficient?signal-to-noise ratios (S/Ns) to place meaningful constraints on ring parameters, we find that six systems with higher S/Ns are inconsistent with the presence of a ring larger than 1.5 times the planetary radius, assuming a grazing orbit and a tilted ring. Furthermore, we identify five preliminary candidate systems whose light curves exhibit ring-like features. After removing four false positives due to the contamination from nearby stars, we identify KIC 10403228 as a reasonable candidate for a ringed planet. A systematic parameter fit of its light curve with a ringed planet model indicates two possible solutions corresponding to a Saturn-like planet with a tilted ring. There also remain two other?possible scenarios accounting for the data; a circumstellar disk and a hierarchical triple. Due to large uncertain factors, we cannot choose one specific model among the three.
机译:系外行星行星环的探测仍然是系外科学领域中最有吸引力但最具挑战性的目标之一。我们提出了一种方法,该方法通过对长周期行星的过渡光度法来实现对系外环的系统搜索。这种方法学依靠我们开发的精确积分方案来计算环形行星的过渡光曲线。我们从开普勒数据中将该方法应用于89个长周期行星候选者,以便估计和/或设置可能的环参数的上限。尽管我们的大多数样本没有足够的信噪比(S / Ns)来对环参数施加有意义的约束,但我们发现六个具有较高S / Ns的系统与较大的环不一致假设有掠过的轨道和倾斜的环,则其半径是行星半径的1.5倍。此外,我们确定了五个初步候选系统,它们的光曲线呈现出环状特征。在去除了附近恒星污染造成的四个误报之后,我们确定KIC 10403228是环形行星的合理候选者。其光曲线与环形行星模型的系统参数拟合表明,对应于带有倾斜环的类似土星的行星,有两种可能的解决方案。还存在另外两个可能的方案来说明数据。一颗星盘和一个三重层次。由于不确定因素较大,我们无法在这三种模型中选择一种。

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