A SIMPLE METHOD FOR DETECTING PERIODIC SIGNALS IN SPARSE ASTRONOMICALEVENT DATA

We present a simple method to detect periodic signals in sparse astron omical event data. The method is particularly appropriate for gamma-ra y astronomy where the number of available photons is sparse in time an d Poissonian noise dominates the statistics. It is based on an autocor relation function, which provides phase independence. We have implemen ted and successfully applied this method on simulated data. This paper presents some numerical results and a description of the model used t o generate the synthetic data along with a formal definition of the si gnal-to-noise ratio in the generated time series.