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研究生: 林建爭
Chien-Cheng Lin
論文名稱: 從中美掩星計畫資料裡計算古伯帶遮掩背景星的機率以及尋找變星
Probability of Stellar Occultation by KBOs and Identifications of Variable Stars in the TAOS Databases
指導教授: 陳文屏
Wen-ping Chen
口試委員:
學位類別: 碩士
Master
系所名稱: 理學院 - 天文研究所
Graduate Institute of Astronomy
畢業學年度: 95
語文別: 英文
論文頁數: 45
中文關鍵詞: 掩星古伯帶食雙星造父變星
外文關鍵詞: occultations, eclipsing, Cepheids, Kuiper Belt
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  • 我們針對中美掩星計畫的資料進行了以下兩個研究: (1)計算掩星機率,中美掩星計畫的目的是要用偵測遮掩背景恆星的機會來估計古柏帶星體的數量,偵測到掩星事件的機率和實際的情況與偵測能力有關。我們討論的方法包含古柏帶星體的數量大小分佈,在星場中恆星大小及數量的分佈,以及古柏帶星體相對在地球上產生陰影的速度。偵測的能力,跟儀器和觀測環境有關係,月相,天氣,繞射等等......。初步結果顯示對於一千顆恆星、十的四到五次方顆半徑一公里以上古柏帶星體的星場,當兩者相對速度為每秒0.001角秒,用簡單的幾何方法可以得到,觀測一個小時會得到的掩星的次數低於時的負八次方。目前尚未有足夠可信的掩星事件,因此我們還需要多收集資料才能得到更多確定的掩星事件。 (2)尋找新的變星,中美掩星計畫從2005年初到目前為止已經觀測了數十億筆的資料,對研究變星提供了了小至幾秒,大至幾百天的時間尺度的觀測資料。計畫中例行觀測的星場有一百六十七個,我們選了目前拍攝次數達到47次的星場編號151(RA = 17h30m7s, Dec = +27d17''30'')。我們從這三平方度的星場,星等從8到16的範圍選出了86個疑似變星,其中有七個是文獻有記載的週期變星。我們分析了這些疑似變星,從他們的週期和光變曲線,簡單的分類出3個造父變星、天琴座c型變星3個、ab型2個、4個食雙星 系統以及5個長週期的變星。


    We have studied the stellar occultation probability calculation and searching for unknown variable stars in the Taiwanese-American Occultation Survey (TAOS) data. Our work is divided into two parts : (1) Stellar occultation probability calculation: Stellar occultation provides currently the only mean to detect small Kuiper-belt objects (KBOs). The number of detection of such events depends on the actual occurrence rate and the detectability. The event rate is determined by the distributed population of the KBOs, the surface number density of background stars, their angular sizes, and the relative shadow speed. The detectability of any event is related to the instruments and circumstances, such as the detector integration time, sampling rate, moon phase, sky variations, diffraction effect, etc. Here we report the computation of the probability of stellar occultation by KBOs from a geometric consideration. With a density of 1000 stars and 103.5 to 105.5 KBOs deg-2, and a relative shadow speed of 0.001” s-1, one expects about 10-8 stellar occultation events by KBOs to take place per hour of bservation. (2) Searching for unknown variable stars: The TAOS project has collected more than a billion photometric measurements since 2005 January. These sky survey data — covering timescales from a few hundred milliseconds to a few hundred days — are a powerful source to study stellar variability. There are 167 star fields monitored by TAOS. Here we summarize the first results of a search for periodic variable stars on one particular filed No. 151 (RA=17h30m7s, Dec=+27d17’30”), which has been observed at 47 epochs. In about a 3 deg square field, between 8 and 16 magnitude, we identified 89 candidate variables, among which only 7 are previously known. We present the analysis methodology for variability and show the light curves for the newly found variables, including 3 Cepheid, 3 RR Lyrae c type, 2 RR Lyrae ab type, 4 eclipsing binaries, and 5 long-period variables.

    1 Introduction 1 1.1 Kuiper Belt Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Taiwan-America Occultation Project . . . . . . . . . . . . . . . . . . . . . 2 1.2.1 Occultation Probability in the TAOS Project . . . . . . . . . . . . . 3 1.2.2 Finding Variable Stars in the TAOS Data . . . . . . . . . . . . . . 4 2 Occultation Probability 5 2.1 Computation of Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Angular Size of KBO, k . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 Angular Size of Background Stars, . . . . . . . . . . . . . . . . . . . . . 8 2.4 Relative Shadow Speed, Vk . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.5 Expected Event Rate by TAOS . . . . . . . . . . . . . . . . . . . . . . . . 11 3 Variable Stars in The TAOS Project 15 3.1 TAOS Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.1.1 Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.1.2 Data Analysis and Calibration . . . . . . . . . . . . . . . . . . . . . 16 3.2 Searching for Unknown Variable Stars . . . . . . . . . . . . . . . . . . . . 18 3.2.1 Variable Identification . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.2.2 Period Determination and Classification . . . . . . . . . . . . . . . 25 3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 4 Conclusion 40 4.1 Probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.2 Variable Stars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 5 Bibliography 43

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