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研究生: 游惟翔
Yu, Wei-Hsiang
論文名稱: 以 Twinkle 望遠鏡之模擬資料研究 K2-21 多行星系統
Studying the K2-21 Multi-Planet System through the Simulated Twinkle Data
指導教授: 江瑛貴
Jiang, Ing-Guey
口試委員: 葉麗琴
Yeh, Li-Chin
陳林文
Chen, Lin-Wen
學位類別: 碩士
Master
系所名稱: 理學院 - 物理學系
Department of Physics
論文出版年: 2023
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: Exoplanet, Transit, Light curves, Transit-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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