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作者(中文):游惟翔
作者(外文):Yu, Wei-Hsiang
論文名稱(中文):以 Twinkle 望遠鏡之模擬資料研究 K2-21 多行星系統
論文名稱(外文):Studying the K2-21 Multi-Planet System through the Simulated Twinkle Data
指導教授(中文):江瑛貴
指導教授(外文):Jiang, Ing-Guey
口試委員(中文):葉麗琴
陳林文
口試委員(外文):Yeh, Li-Chin
Chen, Lin-Wen
學位類別:碩士
校院名稱:國立清華大學
系所名稱:物理學系
學號:110022513
出版年(民國):112
畢業學年度:111
語文別:英文
論文頁數:45
中文關鍵詞:系外行星凌星光變曲線凌星時間變化
外文關鍵詞:ExoplanetTransitLight curvesTransit-Timing Variations
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Twinkle太空望遠鏡將監測眾多擁有系外行星的恆星,透過觀測其發生的行星凌星現象,以研究系外行星的大氣層及獲得高精度的凌星時間中點。為了了解未來的Twinkle太空望遠鏡凌星數據,是否能提昇行星質量的測量精確度,我們以高斯光子雜訊模擬出Twinkle的合成光變曲線,並研究從光變曲線擬合中影響凌星時間中點的誤差來源。已知擁有兩顆行星的K2-21行星系統被用來作為分析例子。這些結果將有助於未來Twinkle在選擇與安排觀測目標和計劃上。
Twinkle Space Telescope will monitor numerous planet-hosting stars during their planet transit events in order to investigate the exoplanet atmospheres and obtain high-precision transit timings. To understand how much the uncertainty of planetary masses of multi-planet systems can be narrowed down by the future Twinkle transit data, the synthetic Twinkle light curves with Gaussian photon noise are generated. The sources of error in mid-transit time derived from light-curve fitting are studied. K2-21 planetary system with two planets is employed as an example. These results will be helpful for Twinkle target selection and observation planning.
Contents . . . . . . . . . . . . . . . . . . . . . . . . . . ii
List of Tables . . . . . . . . . . . . . . . . . . . . . . . iii
List of Figures. . . . . . . . . . . . . . . . . . . . . . . v

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . 1

2 Data . . . . . .. . . . . . . . . . . . . . . . . . . . . . 6
2.1 Twinkle Stardrive - Planet’s Catalog Database . . . . . . 6
2.2 The Planetary System: K2-21 . . . . . . . . . . . . . . . 7

3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.1 Generating Synthetic Light Curves . . . . . . . . . . . . 11
3.1.1 Observable Times . . . . . . . . . . . . . . . . . . . . 12
3.1.2 Passbands . . . . . . . . . . . . . . . . . . . . . . . 13
3.1.3 Exposure Times . . . . . . . . . . . . . . . . . . . . . 17
3.1.4 Data Binning Sizes . . . . . . . . . . . . . . . . . . . 18
3.1.5 The Mid-Transit Time Fitting . . . . . . . . . . . . . . 18
3.2 The Modeling of the Transit-Timing-Variation . . . . . . . 19
3.2.1 Model Descriptions . . . . . . . . . . . . . . . . . . . 19
3.2.2 Markov Chain Monte Carlo Methods. . . . . . . . . . . . . 22

4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.1 Synthetic Light Curves of K2-21 . . . . . . . . . . . . . 25
4.2 The Transit-Timing-Variation of K2-21 . . . . . . . . . . 31

5 Conclusions & FutureWorks . . . . . . . . . . . . . . . . . 38
5.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . 38
5.2 FutureWorks . . . . . . . . . . . . . . . . . . . . . . . 40
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