Data calibration for the MASCARA and bRing instruments

Abstract

Aims: MASCARA and bRing are photometric surveys designed to detect variability caused by exoplanets in stars with $m_V < 8.4$. Such variability signals are typically small and require an accurate calibration algorithm, tailored to the survey, in order to be detected. This paper presents the methods developed to calibrate the raw photometry of the MASCARA and bRing stations and characterizes the performance of the methods and instruments. Methods: For the primary calibration a modified version of the coarse decorrelation algorithm is used, which corrects for the extinction due to the earth's atmosphere, the camera transmission, and intrapixel variations. Residual trends are removed from the light curves of individual stars using empirical secondary calibration methods. In order to optimize these methods, as well as characterize the performance of the instruments, transit signals were injected in the data. Results: After optimal calibration an RMS scatter of 10 mmag at $m_V \sim 7.5$ is achieved in the light curves. By injecting transit signals with periods between one and five days in the MASCARA data obtained by the La Palma station over the course of one year, we demonstrate that MASCARA La Palma is able to recover 84.0, 60.5 and 20.7% of signals with depths of 2, 1 and 0.5% respectively, with a strong dependency on the observed declination, recovering 65.4% of all transit signals at $δ> 0^\circ$ versus 35.8% at $δ< 0^\circ$. Using the full three years of data obtained by MASCARA La Palma to date, similar recovery rates are extended to periods up to ten days. We derive a preliminary occurrence rate for hot Jupiters around A-stars of ${>} 0.4 \%$, knowing that many hot Jupiters are still overlooked. In the era of TESS, MASCARA and bRing will provide an interesting synergy for finding long-period (${>} 13.5$ days) transiting gas-giant planets around the brightest stars.