A Fast Periodicity Detection Algorithm Sensitive to Arbitrary Waveforms

Abstract A reexamination of period-finding algorithms is prompted by new large-area astronomical sky surveys that can identify billions of individual sources having a thousand or more observations per source. This large increase in data necessitates fast and efficient period detection algorithms. In this paper, we provide an initial description of an algorithm that is being used for the detection of periodic behavior in a sample of 1.5 billion objects using light curves generated from Zwicky Transient Facility (ZTF) data. We call this algorithm “Fast Periodicity Weighting” (FPW), derived using a Gaussian Process formalism. Periodic sources in ZTF show a wide variety of waveforms, some quite complex, including eclipsing objects, sinusoidally varying objects also exhibiting eclipses, objects with cyclotron emission at various phases, and accreting objects with complex waveforms. A major advantage of the FPW algorithm is that it is sensitive to a broad range of waveforms. We describe the FPW algorithm and its application to ZTF, and provide efficient code for both CPU and GPU.