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gaia data release 3 documentation

10.10 Planetary transits

10.10.3 Processing steps

Gaia photometry is unevenly sampled and highly sparse, with an average of 14 photometric measurements per star each year. A new implementation of the Box-fitting Least Squares algorithm (Kovács et al. 2002) called SparseBLS (Panahi and Zucker 2021a, b) was used, with increased detection efficiency and reduced run time. SparseBLS ran on the initial candidates, taking normalized G, GBP, and GRP as input, and scanning periods in the range [0.5,100] days with a frequency step of Δf=10-5d-1. We ranked the results by using the signal detection efficiency (SDE) (Kovács et al. 2002; Alcock et al. 2000a) statistic along with a score we call the transit signal-to-noise ratio (TSNR):


where d is the transit_depth, σoot is the standard deviation of the out-of-transit points, and Nit is the number of points in-transit (num_in_transit). In order to find the most promising candidates we applied the following criteria:

  1. 1.


  2. 2.

    TSNR >7.5,

  3. 3.

    transit_depth <40 mmag.

The last criterion was an attempt to avoid cases of eclipsing binaries, or Jovian exoplanets around M dwarfs, which usually have depths greater than 40mmag. The top candidates were then inspected visually.