Radio frequency interference identification using eigenvalue decomposition for multi-beam observations

TL;DR

This paper introduces mRAID, a new eigenvalue decomposition-based RFI detection method for multi-beam radio telescope data, significantly improving efficiency and accuracy in identifying interference during pulsar and FRB searches.

Contribution

The paper presents a novel RFI mitigation package, mRAID, utilizing eigenvalue decomposition for effective, parallelizable interference detection in large-scale radio telescope surveys.

Findings

mRAID effectively identifies RFI in high-resolution pulsar data.

It offers computational advantages over existing methods.

Demonstrates high performance on FAST telescope data.

Abstract

With the installation of next-generation phased array feed (PAF) receivers on radio telescopes, there is an urgent need to develop effective and computationally efficient radio frequency interference (RFI) mitigation methods for large-scale surveys. Here we present a new RFI mitigation package, called mRAID (multi-beam RAdio frequency Interference Detector), which uses the eigenvalue decomposition algorithm to identify RFI in cross-correlation matrix (CCM) of data recorded by multiple beams. When applied to high time-resolution pulsar search data from the Five-hundred-meter Aperture Spherical Radio Telescope (FAST), mRAID demonstrates excellent performance in identifying RFI over short timescales, thereby enhancing the efficiency of pulsar and fast radio burst (FRB) searches. Since the computation of the CCM and the eigenvalue decomposition for each time sub-integration and frequency channel are independent, the process is fully parallelisable. As a result, mRAID offers a significant computational advantage over commonly used RFI detection methods.