Efficiently combining Alpha CenA multi-epoch high-contrast imaging data. Application of K-Stacker to the 80 hrs NEAR campaign
Herv\'e Le Coroller, Mathias Nowak, Kevin Wagner, Markus Kasper, Gael, Chauvin, Celia Desgrange, Simon Conseil

TL;DR
This paper demonstrates the use of the K-Stacker algorithm to re-analyze high-contrast imaging data of Alpha Cen A, improving detection capabilities for potential Earth-like planets by accounting for orbital motion across multiple epochs.
Contribution
The study applies the K-Stacker algorithm to NEAR campaign data, showing its effectiveness in combining multi-epoch observations and constraining orbital parameters of potential planets.
Findings
Detected a single planet candidate consistent with previous reports.
Re-analyzed data with K-Stacker enhances detection of planets with orbital motion.
Future surveys could optimize observation timing using K-Stacker for better orbital constraints.
Abstract
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…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Spectroscopy and Laser Applications
