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.

中文翻译：

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稀疏框拟合最小二乘法

我们提出了一种常用的框拟合最小二乘 (BLS) 算法的新实现，用于检测光度数据中的凌日系外行星。与 BLS 不同，我们的新实现——稀疏 BLS，不使用将数据分箱到相位箱中，也不使用任何类型的相位网格。因此，它的检测效率不依赖于传输阶段，因此略好于 BLS。对于稀疏数据，它也明显比 BLS 快。因此，它非常适合产生不均匀采样的稀疏光变曲线的大型光度测量，例如 Gaia。