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arXiv 1706.06602astro-ph.EP
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60个非过境热木星候选者的监督学习检测

Supervised Learning Detection of Sixty Non-Transiting Hot Jupiter Candidates

Sarah Millholland, Gregory Laughlin

摘要:

短周期行星的光学全相位光度变化提供了行星大气成分和动力学的独特视角。然而,目前具有光学相位曲线探测的行星数量太少,无法将其作为一个总体进行研究,这促使将搜索范围扩大到非凌日行星。在这里,我们提出了一个算法的非过境,短周期的巨行星在开普勒领域的检测。该程序使用相位曲线本身作为行星存在的证据。我们采用监督学习算法来识别合成相位曲线的显着的时间依赖性,然后我们搜索匹配这些属性的信号的检测。在展示了算法的能力之后,我们对142,630颗没有确认行星或KOI的FGK开普勒恒星进行了分类,并为每一颗恒星分配了一个非过境行星相位曲线存在的概率。我们确定了60个高概率的非过境热木星候选者。我们还推导出候选人的相位曲线最大值的偏移量和偏移量的约束。这些目标是后续径向速度确认和表征的强有力的候选者。一旦得到确认,就可以更详细地研究相位曲线中的大气信息内容。

英文摘要:

The optical, full-phase photometric variations of a short-period planet provide a unique view of the planet's atmospheric composition and dynamics. The number of planets with optical phase curve detections, however, is currently too small to study them as an aggregate population, motivating an extension of the search to non-transiting planets. Here we present an algorithm for the detection of non-transiting, short-period giant planets in the Kepler field. The procedure uses the phase curves themselves as evidence for the planets' existence. We employ a supervised learning algorithm to recognize the salient time-dependent properties of synthetic phase curves; we then search for detections of signals that match these properties. After demonstrating the algorithm's capabilities, we classify 142,630 FGK Kepler stars without confirmed planets or KOIs and, for each one, assign a probability of a phase curve of a non-transiting planet being present. We identify 60 high-probability non-transiting hot Jupiter candidates. We also derive constraints on the candidates' albedos and offsets of the phase curve maxima. These targets are strong candidates for follow-up radial velocity confirmation and characterization. Once confirmed, the atmospheric information content in the phase curves may be studied in yet greater detail.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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