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GERBLS—A Rapid Box Least Squares Algorithm for Exoplanet Detection That Scales Well for Large Datasets

  • Authors: Kristo Ment, Eric B. Ford, Suvrath Mahadevan, Rachel B. Fernandes, Andrew Hotnisky

Kristo Ment et al 2026 The Astronomical Journal 172 .

  • Provider: AAS Journals

Caption: Figure 7.

For injected signals recovered by both AstroPy BLS and GERBLS, the distribution of recorded S/N values from the two BLS algorithms. On average, the BLS-recorded S/N values are lower than the initial injected S/N values of those same signals by 0.05 for GERBLS and by 0.25 for AstroPy BLS, leading to an average S/N offset of 0.20 between the two shown distributions. S/N values can decrease during recovery due to the discreteness of the BLS parameter grid as well as noise in the data, but the decrease is steeper for the brute-force AstroPy BLS.

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