The DOHA algorithm: A new recipe for cotrending large-scale transiting exoplanet survey light curves

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

We present DOHA, a new algorithm for cotrending photometric light curves obtained by transiting exoplanet surveys. The algorithm employs a novel approach to the traditional 'differential photometry' technique, by selecting the most suitable comparison star for each target light curve, using a two-step correlation search. Extensive tests on real data reveal that DOHA corrects both intra-night variations and long-term systematics affecting the data. Statistical studies conducted on a sample of ~9500 light curves from the Qatar Exoplanet Survey reveal that DOHA-corrected light curves show an rms improvement of a factor of ~2, compared to the raw light curves. In addition, we show that the transit detection probability in our sample can increase considerably, even up to a factor of 7, after applying DOHA.

Original languageEnglish
Pages (from-to)3759-3766
Number of pages8
JournalMonthly Notices of the Royal Astronomical Society
Volume465
Issue number3
DOIs
Publication statusPublished - 2017

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extrasolar planets
light curve
Qatar
transit
night
photometry
stars

Keywords

  • Methods: data analysis
  • Methods: statistical
  • Planets and satellites: detection
  • Techniques: photometric

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

Cite this

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title = "The DOHA algorithm: A new recipe for cotrending large-scale transiting exoplanet survey light curves",
abstract = "We present DOHA, a new algorithm for cotrending photometric light curves obtained by transiting exoplanet surveys. The algorithm employs a novel approach to the traditional 'differential photometry' technique, by selecting the most suitable comparison star for each target light curve, using a two-step correlation search. Extensive tests on real data reveal that DOHA corrects both intra-night variations and long-term systematics affecting the data. Statistical studies conducted on a sample of ~9500 light curves from the Qatar Exoplanet Survey reveal that DOHA-corrected light curves show an rms improvement of a factor of ~2, compared to the raw light curves. In addition, we show that the transit detection probability in our sample can increase considerably, even up to a factor of 7, after applying DOHA.",
keywords = "Methods: data analysis, Methods: statistical, Planets and satellites: detection, Techniques: photometric",
author = "Dimitrios Mislis and S. Pyrzas and Khalid Al-Subai and Zlatan Tsvetanov and Vilchez, {N. P E}",
year = "2017",
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language = "English",
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journal = "Monthly Notices of the Royal Astronomical Society",
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publisher = "Oxford University Press",
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TY - JOUR

T1 - The DOHA algorithm

T2 - A new recipe for cotrending large-scale transiting exoplanet survey light curves

AU - Mislis, Dimitrios

AU - Pyrzas, S.

AU - Al-Subai, Khalid

AU - Tsvetanov, Zlatan

AU - Vilchez, N. P E

PY - 2017

Y1 - 2017

N2 - We present DOHA, a new algorithm for cotrending photometric light curves obtained by transiting exoplanet surveys. The algorithm employs a novel approach to the traditional 'differential photometry' technique, by selecting the most suitable comparison star for each target light curve, using a two-step correlation search. Extensive tests on real data reveal that DOHA corrects both intra-night variations and long-term systematics affecting the data. Statistical studies conducted on a sample of ~9500 light curves from the Qatar Exoplanet Survey reveal that DOHA-corrected light curves show an rms improvement of a factor of ~2, compared to the raw light curves. In addition, we show that the transit detection probability in our sample can increase considerably, even up to a factor of 7, after applying DOHA.

AB - We present DOHA, a new algorithm for cotrending photometric light curves obtained by transiting exoplanet surveys. The algorithm employs a novel approach to the traditional 'differential photometry' technique, by selecting the most suitable comparison star for each target light curve, using a two-step correlation search. Extensive tests on real data reveal that DOHA corrects both intra-night variations and long-term systematics affecting the data. Statistical studies conducted on a sample of ~9500 light curves from the Qatar Exoplanet Survey reveal that DOHA-corrected light curves show an rms improvement of a factor of ~2, compared to the raw light curves. In addition, we show that the transit detection probability in our sample can increase considerably, even up to a factor of 7, after applying DOHA.

KW - Methods: data analysis

KW - Methods: statistical

KW - Planets and satellites: detection

KW - Techniques: photometric

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