论文标题
模拟预测多色同时光度法将苔丝候选系外行星与假阳性区分开的能力
Simulations Predicting the Ability of Multi-Color Simultaneous Photometry to Distinguish TESS Candidate Exoplanets from False Positives
论文作者
论文摘要
过境系外行星调查卫星（TESS）目前正在结束其为期两年的初级科学任务，搜索了85％的天空，以进行过境的系外行星。苔丝已经发现了一千多个感兴趣的苔丝对象（TOIS），但是这些候选系外行星必须与使用其他工具或技术的天体物理误报区分开来。可以使用3频段多色同时摄像机研究过境行星的气氛（Muscat）以及4频段的Muscat2，可用于验证苔丝发现。当在多个带通中观察到外型球星的转运是具有成本性的，而假阳性的过境深度通常随波长而变化。我们创建了软件工具，以模拟Muscat/Muscat2 Tess随访观察结果，并揭示哪些行星候选者可以有效地与使用这两种仪器混合二进制（BEB）误报的混合，并且必须使用其他技术进行验证。我们将软件代码应用于Barclay等人。 （2018）预测了苔丝发现，以及从Exofop-Tess网站下载的Tois。我们估计Muscat（括号中的Muscat2值）将能够使用其多色能力来区分所有苔丝发现中的$ \ sim $ 17％（$ \ sim $ 18％）的Beb误报，$ \ sim $ \ sim $ 13％（$ \ sim $ 15％）的$ r _ _ {\ r _ \ rm pl}我们的TOI分析表明，Muscat（MUSCAT2）可以以$ \ sim $ \ sim $ \ sim $ 55％（$ \ sim $ 52％）的Tois区分误差，其过境深度大于0.001，以$ \ sim $ \ sim $ 64％（$ \ sim $ \ sim $ 61％）的tois tois tois toiss $ $ $ 70％（$ \ sim $ 61％），以及$ 70％（$ 70％）（$ 70％）深度大于0.003。我们的工作表明Muscat和Muscat2可以验证数百个$ r _ {\ rm pl} <4r_ \ oplus $候选外部球队，从而支持达到苔丝的任务，以达到其1级科学要求。
The Transiting Exoplanet Survey Satellite (TESS) is currently concluding its 2-year primary science mission searching 85% of the sky for transiting exoplanets. TESS has already discovered well over one thousand TESS objects of interest (TOIs), but these candidate exoplanets must be distinguished from astrophysical false positives using other instruments or techniques. The 3-band Multi-color Simultaneous Camera for Studying Atmospheres of Transiting Planets (MuSCAT), as well as the 4-band MuSCAT2, can be used to validate TESS discoveries. Transits of exoplanets are achromatic when observed in multiple bandpasses, while transit depths for false positives often vary with wavelength. We created software tools to simulate MuSCAT/MuSCAT2 TESS follow-up observations and reveal which planet candidates can be efficiently distinguished from blended eclipsing binary (BEB) false positives using these two instruments, and which must be validated using other techniques. We applied our software code to the Barclay et al. (2018) predicted TESS discoveries, as well as to TOIs downloaded from the ExoFOP-TESS website. We estimate that MuSCAT (MuSCAT2 values in parentheses) will be able to use its multi-color capabilities to distinguish BEB false positives for $\sim$17% ($\sim$18%) of all TESS discoveries, and $\sim$13% ($\sim$15%) of $R_{\rm pl} < 4R_\oplus$ discoveries. Our TOI analysis shows that MuSCAT (MuSCAT2) can distinguish BEB false positives for $\sim$55% ($\sim$52%) of TOIs with transit depths greater than 0.001, for $\sim$64% ($\sim$61%) of TOIs with transit depths greater than 0.002, and for $\sim$70% ($\sim$68%) of TOIs with transit depth greater than 0.003. Our work shows that MuSCAT and MuSCAT2 can validate hundreds of $R_{\rm pl} < 4R_\oplus$ candidate exoplanets, thus supporting the TESS mission in achieving its Level 1 Science Requirement.
