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The Next Generation Transit Survey (NGTS), operating in Paranal since 2016,is a wide-field survey to detect Neptunes and super-Earths transiting brightstars, which are suitable for precise radial velocity follow-up andcharacterisation. Thereby, its sub-mmag photometric precision and ability toidentify false positives are crucial. Particularly, variable background objectsblended in the photometric aperture frequently mimic Neptune-sized transits andare costly in follow-up time. These objects can best be identified with thecentroiding technique: if the photometric flux is lost off-centre during aneclipse, the flux centroid shifts towards the centre of the target star.Although this method has successfully been employed by the Kepler mission, ithas previously not been implemented from the ground. We present afully-automated centroid vetting algorithm developed for NGTS, enabled by ourhigh-precision auto-guiding. Our method allows detecting centroid shifts withan average precision of 0.75 milli-pixel, and down to 0.25 milli-pixel forspecific targets, for a pixel size of 4.97 arcsec. The algorithm is now part ofthe NGTS candidate vetting pipeline and automatically employed for all detectedsignals. Further, we develop a joint Bayesian fitting model for all photometricand centroid data, allowing to disentangle which object (target or background)is causing the signal, and what its astrophysical parameters are. Wedemonstrate our method on two NGTS objects of interest. These achievements makeNGTS the first ground-based wide-field transit survey ever to successfullyapply the centroiding technique for automated candidate vetting, enabling theproduction of a robust candidate list before follow-up.

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