The False Alarm Probability (FAP) is a metric to express the significance of a period. A False Alarm arises in period analysis techniques when incorrectly a period is found where none exists in reality. The lower the FAP for a given period P, the more likely P is a significant period. FAP values are expressed as a number between 0 and 1.

As a rule of thumb : FAPs below 0.01 (1%) mostly indicate very secure periods, and those between 0.01 and 0.20 are far less certain. Anything above 0.20 (20%) mostly relates to an artifact in your data, instead of a true period. 

Peranso calculates two FAPs as part of a period significance analysis for a given period P. The first FAP is the probability that there is no period in the Period Window with value P. The second FAP is the probability that the observations contain a period that is different from P.

The Generalized Lomb-Scargle method uses a different approach to calculating FAP values, as explained in the corresponding section.