The Generalized Lomb-Scargle (GLS) periodogram was introduced by Zechmeister & Kürster1 in 2009. Compared to the 'classical' Lomb-Scargle periodogram, the GLS takes into account measurement (brightness) errors and a constant term in the fit of the wave function. As a result, GLS provides more accurate frequencies, is less susceptible to aliasing, and gives a much better determination of the spectral intensity.

Peranso furthermore calculates and shows three False Alarm Probability (FAP) levels to help distinguish between significant and spurious peaks. We compute FAP levels of 10%, 5%, and 1%, which are visually represented in the Period Window by resp. an orange, green and red colored dashed horizontal line. The computation of these FAP levels is different from the standard FAP method supported by Peranso, which uses a Monte Carlo Permutation Procedure in order to determine FAP levels. This is much more time-consuming than the actual FAP computations through the GLS.  

The Lomb-Scargle GLS dialog box is similar to the Lomb-Scargle dialog box.  Prominent periods of the Period Window appear as peaks.

Generalized Lomb-Scargle (GLS) False Alarm Probability

The GLS FAP denotes the probability that at least one out of M independent power values P in a prescribed search band of a power spectrum computed from a white-noise time series is as large as or larger than the threshold, Pn. It is given by:

                 FAP(Pn) = 1 - [1 - Prob(P>Pn)]M


- M is the number of independent power values. It is computed internally but may be estimated as the number of peaks in the periodogram
- Prob(P>Pn) is the probability function. Many probability functions exist in literature, depending on the type of periodogram and normalization. 
- Pn is the power treshold

(1) M. Zechmeister & M. Kürster, The generalised Lomb-Scargle periodogram. A New formalism for the floating-mean and Keplerian periodograms, 2009, A&A, 496, 577