The BAST algorithm for transit detection
S. Renner, H. Rauer, A. Erikson, P. Hedelt, P. Kabath, R. Titz, H., Voss

TL;DR
BAST is a fast and efficient algorithm for detecting periodic transits in stellar light curves, comparable to BLS in performance but significantly faster, capable of identifying Earth-sized exoplanets in low-noise data.
Contribution
The paper introduces BAST, a new transit detection algorithm that is faster than BLS and effective in identifying small exoplanets in simulated CoRoT data.
Findings
BAST performs similarly to BLS at high signal-to-noise ratios.
BAST is ten times faster than BLS in transit detection.
Detects Earth-sized planets with transit depths around 0.01% in low-noise data.
Abstract
The pioneer space mission for photometric exoplanet searches, CoRoT, steadily monitors about 12000 stars in each of its fields of view. Transit detection algorithms are applied to derive promising planetary candidates, which are then followed-up with ground-based observations. We present BAST (Berlin Automatic Search for Transits), a new algorithm for periodic transit detection, and test it on simulated CoRoT data. BAST searches for box-shaped signals in normalized, filtered, variability-fitted, and unfolded light curves. A low-pass filter is applied to remove high-frequency signals, and linear fits to subsections of data are subtracted to remove the star's variability. A search for periodicity is then performed in transit events identified above a given detection threshold. Some criteria are defined to better separate planet candidates from binary stars. From the analysis of…
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