Real-Time RFI Mitigation for the Apertif Radio Transient System

Abstract

Current and upcoming radio telescopes are being designed with increasing sensitivity to detect new and mysterious radio sources of astrophysical origin. While this increased sensitivity improves the likelihood of discoveries, it also makes these instruments more susceptible to the deleterious effects of Radio Frequency Interference (RFI). The challenge posed by RFI is exacerbated by the high data-rates achieved by modern radio telescopes, which require real-time processing to keep up with the data. Furthermore, the high data-rates do not allow for permanent storage of observations at high resolution. Offline RFI mitigation is therefore not possible anymore. The real-time requirement makes RFI mitigation even more challenging because, on one side, the techniques used for mitigation need to be fast and simple, and on the other side they also need to be robust enough to cope with just a partial view of the data.The Apertif Radio Transient System (ARTS) is the real-time, time-domain, transient detection instrument of the Westerbork Synthesis Radio Telescope (WSRT), and it is a perfect example of this challenging scenario. This system processes 73 Gb of data per second, in real-time, searching for faint pulsars and Fast Radio Bursts. Despite the radio quiet zone around WSRT, the generation of RFI is becoming increasingly part of anthropic activities, especially in a densely populated environment like the Netherlands where the telescope is located. Furthermore, our sky is populated by a growing number of satellites for world-wide telecommunication. Hence, the ARTS pipeline requires state-of-the-art real-time RFI mitigation, even if it contains a deep learning classifier to reduce the number of false-positive detections.Our solution to this challenge is RFIm, a high-performance, open-source, tuned, and extensible RFI mitigation library. The goal of this library is to provide users with RFI mitigation routines that are designed to run in real-time on many-core accelerators, such as Graphics Processing Units, and that can be highly-tuned to achieve code and performance portability to different hardware platforms and scientific use-cases. Results on ARTS show that we can achieve real-time RFI mitigation, with a minimal impact on the total execution time of the search pipeline, and considerably reduce the number of false-positives.