Sparse box-fitting least squares

Aviad Panahi, Shay Zucker

Research output: Contribution to journalArticlepeer-review


We present a new implementation of the commonly used Box-fitting Least Squares (BLS) algorithm, for the detection of transiting exoplanets in photometric data. Unlike BLS, our new implementation—Sparse BLS, does not use binning of the data into phase bins, nor does it use any kind of phase grid. Thus, its detection efficiency does not depend on the transit phase, and is therefore slightly better than that of BLS. For sparse data, it is also significantly faster than BLS. It is therefore perfectly suitable for large photometric surveys producing unevenly-sampled sparse light curves, such as Gaia.

Original languageEnglish
Article number024502
Pages (from-to)1-6
Number of pages6
JournalPublications of the Astronomical Society of the Pacific
Issue number1020
StatePublished - 1 Feb 2021


  • Algorithms
  • Astronomy data analysis
  • Exoplanet detection methods
  • Transit photometry


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