A signal dedispersion algorithm for imaging-based transient searches

Abstract

Dedispersion is the computational process of correcting for the frequency-dependent time delay affecting a radio signal that propagates through the interstellar and intergalactic media. It is a crucial component of transient search pipelines that maximises the signal-to-noise ratio, especially when targeting highly dispersed signals: for instance, pulsar emissions making their way through a dense cloud of ionised gas, and fast radio bursts travelling cosmological distances. This paper introduces Streaming high Time-Resolution Imaging DEdispersion (STRIDE), a novel dedispersion algorithm to generate per-pixel dedispersed time series from high time and frequency resolution interferometric images. Unlike straightforward approaches to image dedispersion, STRIDE does not involve expensive manipulation of the input data layout, such as explicitly building dynamic spectra or shifting images. Furthermore, it is the first dedispersion algorithm to partition a dispersive sweep over the time dimension, in addition to frequency. As a consequence, images corresponding to the entire time span of the target dispersive delay are not required all at once. Instead, the algorithm works with an arbitrarily-sized subset of images at a time, adopting an incremental, streaming-based approach to dedispersion. In evaluating STRIDE on the presented test case, it is shown that the minimum memory requirement is reduced by 97.9%, going from 684.5 GB to 14.4 GB. As current and future generations of widefield interferometers increasingly turn to imaging techniques for detection and localisation of radio transients, STRIDE positions itself as a strong alternative to traditional dedispersion methodologies. It arguably is the only viable option for imaging-based searches with low-frequency instruments such as the Murchison Widefield Array (MWA) and low-frequency Square Kilometre Array (SKA-Low).