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Centroid vetting of transiting planet candidates from the Next Generation Transit Survey

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posted on 2017-08-02, 11:20 authored by Maximilian N. Günther, Didier Queloz, Edward Gillen, James McCormac, Daniel Bayliss, Francois Bouchy, Simon R. Walker, Richard G. West, Philipp Eigmüller, Alexis M. S. Smith, David J. Armstrong, Matthew Burleigh, Sarah L. Casewell, Alexander P. Chaushev, Michael R. Goad, Andrew Grange, James Jackman, James S. Jenkins, Tom Louden, Maximiliano Moyano, Don Pollacco, Katja Poppenhaeger, Heike Rauer, Liam Raynard, Andrew P. G. Thompson, Stéphane Udry, Christopher A. Watson, Peter J. Wheatley
The Next Generation Transit Survey (NGTS), operating in Paranal since 2016, is a wide-field survey to detect Neptunes and super-Earths transiting bright stars, which are suitable for precise radial velocity follow-up and characterisation. Thereby, its sub-mmag photometric precision and ability to identify false positives are crucial. Particularly, variable background objects blended in the photometric aperture frequently mimic Neptune-sized transits and are costly in follow-up time. These objects can best be identified with the centroiding technique: if the photometric flux is lost off-centre during an eclipse, the flux centroid shifts towards the centre of the target star. Although this method has successfully been employed by the Kepler mission, it has previously not been implemented from the ground. We present a fully-automated centroid vetting algorithm developed for NGTS, enabled by our high-precision auto-guiding. Our method allows detecting centroid shifts with an average precision of 0.75 milli-pixel, and down to 0.25 milli-pixel for specific targets, for a pixel size of 4.97 arcsec. The algorithm is now part of the NGTS candidate vetting pipeline and automatically employed for all detected signals. Further, we develop a joint Bayesian fitting model for all photometric and centroid data, allowing to disentangle which object (target or background) is causing the signal, and what its astrophysical parameters are. We demonstrate our method on two NGTS objects of interest. These achievements make NGTS the first ground-based wide-field transit survey ever to successfully apply the centroiding technique for automated candidate vetting, enabling the production of a robust candidate list before follow-up.


This research is based on data collected under the NGTS project at the ESO La Silla Paranal Observatory. NGTS is operated with support from an UK Science and Technology Facilities Council (STFC) research grant (ST/M001962/1). This work has further made use of data from the European Space Agency (ESA) mission Gaia (, processed by the Gaia Data Processing and Analysis Consortium (DPAC, Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. Moreover, this publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. We also make use of the open-source Python packages numpy (van der Walt et al. 2011), scipy (Jones et al. 2001), matplotlib (Hunter 2007), pandas (McKinney 2010), emcee (Foreman-Mackey et al. 2013), corner (Foreman-Mackey 2016), and eb (Irwin et al. 2011). The latter is based on the previous JKTEBOP (Southworth et al. 2004a,b) and EBOP codes (Popper & Etzel 1981), and models by Etzel (1981), Mandel & Agol (2002), Binnendijk (1974a,b), and Milne (1926). DJA is funded under STFC consolidated grant reference ST/P000495/1. MNG is supported by the UK Science and Technology Facilities Council (STFC) award reference 1490409 as well as the Isaac Newton Studentship.



Monthly Notices of the Royal Astronomical Society, 2017, 472 (1), pp. 295–307

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/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Physics and Astronomy


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