Efficiently combining α CenA multi-epoch high-contrast imaging data. Application of K-Stacker to the 80 hours NEAR campaign

Keplerian-Stacker is an algorithm able to combine multiple observations acquired at different epochs taking into account the orbital motion of a potential planet present in the images to boost the ultimate detection limit. In 2019, a total of 100 hours of observation were allocated to VLT VISIR-NEAR, a collaboration between ESO and Breakthrough Initiatives, to search for low mass planets in the habitable zone of the Alpha Cen AB binary system. A weak signal (S/N = 3) was reported around Alpha Cen A, at a separation of 1.1 a.u. which corresponds to the habitable zone. We have re-analysed the NEAR data using K-Stacker. This algorithm is a brute-force method able to find planets in time series of observations and to constrain their orbital parameters, even if they remain undetected in a single epoch. We scanned a total of about 3.5e+5 independent orbits, among which about 15 % correspond to fast moving orbits on which planets cannot be detected without taking into account the orbital motion. We find only a single planet candidate, which matches the C1 detection reported in Wagner et al. 2021. Despite the significant amount of time spent on this target, the orbit of this candidate remains poorly constrained due to these observations being closely distributed in 34 days. We argue that future single-target deep surveys would benefit from a K-Stacker based strategy, where the observations would be split over a significant part of the expected orbital period to better constrain the orbital parameters. This application of K-Stacker on high contrast imaging data in the mid-infrared demonstrates the capability of this algorithm to aid in the search for Earth-like planets in the habitable zone of the nearest stars with future instruments of the E-ELT such as METIS.
9 pages, 11 figures, K-Stacker github link