BAYESIAN PERIODIC SIGNAL-DETECTION - ANALYSIS OF ROSAT OBSERVATIONS OF PSR-0540-693

We briefly summarize the main features of our Bayesian method for dete cting and measuring periodic signals in event arrival time data, and c ompare it to the more common fast Fourier transform (FFT) and epoch fo lding (EF) methods in a case study using ROSAT observations of the X-r ay pulsar PSR 0540-693. Although originally detected using an FFT anal ysis of Einstein Observatory data (Seward, Harnden, & Helfand), the sa me 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 th e Bayesian method. These include the ease of interpretation of the res ults and more accurate period determinations. Furthermore, the Bayesia n approach accounts for our prior uncertainty in the signal period and phase in a manner that does not require specification of the number a nd location of ''independent'' frequencies or phases, an aspect of mor e traditional approaches that lends a troubling subjectivity to conclu sions based on them. Finally, we present the shape of the pulsar light curve derived from the ROSAT data by using our Bayesian method.