AN EFFICIENT ALGORITHM FOR THE DETECTION OF INFREQUENT RAPID BURSTS IN TIME SERIES DATA

摘要

Searching through data for infrequent rapid bursts is a common requirement in many areas of scientific research. In this paper, we present a powerful and flexible analysis method that, in a single pass through the data, searches for statistically significant bursts on a set of specified short timescales. The input data are binned, if necessary, and then quantified in terms of probabilities rather than rates or ratios. Using a measure-like probability makes the method relatively count rate independent. The method has been made computationally efficient by the use of lookup tables and cyclic buffers, and it is therefore particularly well suited to real-time applications. The technique has been developed specifically for use in an X-ray astronomy application to search for millisecond bursts from black hole candidates such as Cyg X-1. We briefly review the few observations of these types of features reported in the literature, as well as the variety of ways in which their statistical reliability was challenged. The developed technique, termed the burst expectation search (BES) method, is illustrated using some data simulations and archived data obtained during ground testing of the proportional counter array (PCA) experiment detectors on the Rossi X-Ray Timing Explorer (RXTE). A potential application for a real-time BES method on board RXTE is also examined.