Uncovering Periods in Astronomical Time Series With Few Data

A procedure for discovering periods in astronomical time series containing few observational data using simple mathematical operations is described. By selecting data close to the maxima or minima of the time series, differences among these values around the maxima or minima are obtained to produce a set of intervals. Using a technique similar to the least common divisor and applying the maximum common denominator to the set of intervals approximate periods are found. The different ways to improve the periods found are presented. The procedure is applied to a simulated random sinusoidal data set and also to some data from binary and pulsating variable stars to show how the procedure is applied to different types of time series. The procedure is simple to use for any type of data spacing and with gaps, and produces results in accordance with other methods.