Bayesian Periodic Signal Detection: Analysis ofROSATObservations of PSR 0540−693

Abstract

We briefly summarize the main features of our Bayesian method for detecting and measuring periodic signals in event arrival time data, and compare it to the more common fast Fourier transform (FFT) and epoch folding (EF) methods in a case study using ROSAT observations of the X-ray pulsar PSR 0540-693. Although originally detected using an FFT analysis of Einstein Observatory data (Seward, Harnden, & Helfand), the same approach failed to detect the pulsar signal in ROSAT data. We show that both EF and our Bayesian method can reliably detect the pulsar in the ROSAT data, and we demonstrate several important advantages of the Bayesian method. These include the ease of interpretation of the results and more accurate period determinations. Furthermore, the Bayesian approach accounts for our prior uncertainty in the signal period and phase in a manner that does not require specification of the number and location of independent frequencies or phases, an aspect of more traditional approaches that lends a troubling subjectivity to conclusions based on them. Finally, we present the shape of the pulsar light curve derived from the ROSAT data by using our Bayesian method.