  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 (SBLS), 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.
