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Department of Physics and Astronomy Department of Physics and Astronomy University of Heidelberg Master thesis in Physics submitted by Minjae Kim born in Seoul, South Korea 2015 Preparation of the CARMENES target list This Master thesis has been carried out by Minjae Kim at the Landessternwarte Königstuhl Zentrum für Astronomie der Universität Heidelberg under the supervision of Prof. Dr. Andreas Quirrenbach & Dr. José A. Caballero (Centro de Astrobiología, Madrid, Spain) Vorbereitung des CARMENES Zielliste Zusammenfassung Kontext: CARMENES ist eine Technologie der nächsten Generation, die durch ein Konsortium aus zahlreichen spanischen und deutschen Instituten aufgebaut wird, um eine Durchmusterung von 300 Sternen der M-Klasse durchzuführen mit dem Ziel, Exo-Erden durch Radialgeschwindigkeitsvermessungen zu entdecken. Ziele: Das Hauptziel dieser Masterarbeit besteht darin, Ziellisten für die CARMENES Commisioningvorzu- bereiten und das internationale Konsortium zu unterstützen. Das erste Ziel ist der Entwurf von Star Cards auf CARMENES GTO Websites für alle Alpha Stars in CARMENCITA. Das zweite Ziel ist der Entwurf der definitiven Finding Charts, die sich in der Star Cards für alle Alpha Stars in CARMENCITA wiederfinden wird. Das dritte Ziel ist die Schätzung von zukünftigen Koordinaten für alle 2200 Sternen in CARMENCITA für die CARMENES-Commisioning. Das letzte Ziel liegt in der Feststellung von unterschiedlichen wissenschaftlichen Applikationen und Untersuchungen innerhalb von CARMENCITA zur Unterstützung der CARMENES-Studie. Methoden: Hauptsächlich werden zwei virtual observatory softwares verwendet (Aladin und TOPCAT). Zusätzlich wird Python verwendet zur automatischen Erstellung fehlerfreier Star Cards, sowie zur Berech- nung mit dem Ziel der Schätzung von zukünftigen Koordinaten und der Erstellung von Entwürfen (auch anhand von GNU Octave). MS Office dient zur Erstellung von Finding Charts Templates. IRAF wird verwendet bei der Suche nach engen Doppelsternsystemen mit fotografischen Tafeln aus SuperCOSMOS Sky Survey. Die gesamte Arbeit ist auf CARMENCITA basiert. Ergebnisse: Sowohl 353 Star Cards als auch Finding Charts von allen Alpha Stars in CARMENCITA sind erfolgreich auf unseren CARMENES GTO Websites aktualisiert worden. Schätzungen von zukünftigen Koordinaten während der CARMENES Erhebung (2016.0, 2016.5 and 2018.0) für vollständige 2200 CARMENCITA Sterne und weitere mehrere wissenschaftliche Anwendungen in CARMENCITA werden in dieser Masterarbeit erforscht. Fazit: Diese Arbeit erlaubt die Entwicklung einer Vorbereitung von den CARMENES Ziellisten. Stichwörter: Astronomische Datenbank — Sterne: M-Zwergsterne: CARMENES, CARMENCITA — Sterne: Finding Charts — Sterne: Star-cards Preparation of the CARMENES target list Abstract Context: CARMENES is a next-generation instrument being built by a consortium of German and Spanish institutions to carry out a survey of 300 M-type stars with the goal of detecting exoearths by radial velocity measurements. Aims: The main goal of this MSc thesis is to prepare target lists for CARMENES commissioning and to help the international consortium. The first aim at this thesis is preparation of star cards in CARMENES GTO webpages for all of alpha stars in CARMENCITA. The second aim is definitive finding charts which will be in star cards for all of alpha stars in CARMENCITA. The third aim is the estimation future coordinates for whole 2200 stars in CARMENCITA for CARMENES commissioning. The fourth aim is lots of scientific applications and investigation in CARMENCITA to help CARMENES survey. Methods: It will be mainly used two virtual observatory software (Aladin and TOPCAT) for overall works. Python will be used for generating star-cards automatically without errors, lots of calculation in estimating future coordinates and making plots (with GNU Octave also). MS Office will be used for making finding charts templates. IRAF will be used for searching very close binaries with photographic plates from SuperCOSMOS Sky Survey. Whole works are based on CARMENCITA. Results: Both 353 star cards and finding charts of all of alpha stars in CARMENCITA are successfully updated on our CARMENES GTO webpages. Estimation future coordinates when CARMENES survey (2016.0, 2016.5 and 2018.0) for whole 2200 CARMENCITA stars and lots of other scientific applications in CARMENCITA are investigated in this MSc thesis. Conclusions: These works allow us to develop a preparation of the CARMENES target list. Keywords: Astronomical data bases — Stars: M-dwarf Stars: CARMENES, CARMENCITA — Stars: finding charts — Stars: star-cards 3 Contents 1 Introduction 6 1.1 The search for exoplanets........................................6 1.2 M dwarfs.................................................6 1.3 CARMENES...............................................7 1.4 CARMENCITA..............................................9 1.4.1 Data................................................ 11 1.4.2 Star class in CARMENCITA.................................. 11 1.5 Objectives................................................. 11 2 Analysis 14 2.1 Star cards, HTML table with Python.................................. 14 2.1.1 HTML table........................................... 14 2.1.2 Python.............................................. 14 2.2 Past, present and future coordinates.................................. 14 2.2.1 Past coordinates and proper motion.............................. 15 2.2.2 Present coordinates with WISE data.............................. 16 2.2.3 Future coordinates prediction.................................. 21 2.3 Finding charts.............................................. 22 2.3.1 Acquisition and guiding camera (A&G)............................ 22 2.3.2 Photometric systems and RR band............................... 24 2.3.3 Retrieving SuperCOSMOS digitisations in R band data................... 27 2.3.4 How to make the finding charts................................. 29 2.3.5 Fibre contamination....................................... 33 2.4 Scientific application in CARMENCITA................................ 34 2.4.1 Finding close binaries in IRAF................................. 34 2.4.2 Scientific application in CARMENCITA............................ 36 3 Results and discussion 38 3.1 Star cards................................................. 38 3.2 Estimating coordinate.......................................... 40 3.2.1 WISE coordinates estimate as a current epoch........................ 40 3.2.2 Future coordinate in CARMENES survey........................... 54 3.3 Finding charts.............................................. 54 3.3.1 Finding charts.......................................... 54 3.3.2 Fibre contamination....................................... 57 3.4 Scientific application in CARMENCITA................................ 58 3.4.1 Finding close binaries in IRAF................................. 58 3.4.2 CARMENCITA classification about multiple systems.................... 63 3.4.3 CARMENCITA with wide binaries............................... 64 3.4.4 Spectral type and frequency of companions to our M dwarfs................. 64 3.4.5 Multiple star systems in CARMENCITA........................... 69 3.4.6 Change of CARMENCITA database number......................... 69 4 Conclusions and future work 70 5 Acknowledgment 72 References 73 I Appendix 75 List of Figures 75 List of Tables 76 A M Spectral type stars with exoplanets 78 B HTML sample tables for star cards 81 4 C How to make HTML table samples with Python 86 D Astronomical sky survey 88 E Estimated coordinate in Epoch of 2016.0, 2016.5 and 2018.0. 90 F Wide binaries in CARMENCITA. 131 G CARMENCITA stars with M primaries not in CARMENCITA. 138 5 1 Introduction 1.1 The search for exoplanets Since exoplanets are much fainter than the mother star exoplanets that orbit, they are extremely difficult to detect directly. In addition, direct imaging works best for planets that orbit stars which are nearest to the Sun, and it is particularly sensitive to young and massive planets with only infrared survey. For those reasons, at the present time, there are few indirect methods that have yielded success; therefore, indirect observations are much more commonly used when searching exoplanets. One of the most successful technique for detecting exoplanets so far is the radial velocity method which measures variations in the radial velocity of the star with respect to the Earth. Variations in the radial velocity of the star can be easily detected through displacements in the star’s spectral lines due to the Doppler effect. The first exoplanet around a solar-like star was 51 Pegasi b, discovered by Mayor & Queloz in 1995 with radial velocity techniques after Doppler monitoring. Around 440 planets have been discovered by the radial velocity with Doppler effect method. Discovery rate increased from a few per year to between 50 and 100 per year more recently. The radial velocity semi-amplitude K∗ of a star signal can be expressed in units of [cm/s] with the planet mass in units of M⊕ in the following Equation (1) (Fischer et al. 2014[11]): −1 −2/3 −1/3 8.95cms Mp sin i M∗ + Mp P K∗ = √ (1) 1 − e2 M⊕ M yr If the mass of the star M∗ is known, the observed parameters, velocity semi-amplitude K∗, orbital period P, eccentricity e, and orientation angle ω can be used to calculate the minimum mass of the planet Mp sin i. As the Equation (1) demonstrates, an important aspect of equation is that for a given planetary mass, there are two possibilities that the planetary signal increment. It is clear that the radial velocity amplitude
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