FITrig: A High-Performance Detection Technique for Efficient Ultra-Long-Period Pulsars

TL;DR

This paper tackles the challenge of detecting ultra-long-period pulsars in wide-field radio imaging, where traditional time-domain searches struggle with sensitivity and False Positive rates. It introduces FITrig, a GPU-accelerated, dual-domain method that uses a novel transient-oriented IQA metric, tLISI, to localise pulsar candidates in image and image-frequency domains. The key contributions are the tLISI index, a deconvolution-free, tile-based detection framework, GPU-accelerated implementation, and comprehensive evaluation showing substantial speedups and reduced false positives on real MeerKAT data and simulated SKA configurations. The approach promises real-time applicability to next-generation telescopes and could generalise to broader transient discovery beyond pulsars.

Abstract

Ultra-long-period (ULP) pulsars, a newly identified class of celestial transients, offer unique insights into astrophysics, though very few have been detected to date. In radio astronomy, most time-domain detection methods cannot find these pulsars, and current image-based detection approaches still face challenges, including low sensitivity, high false positive rate, and low computational efficiency. In this article, we develop Fast Imaging Trigger (FITrig), a GPU-accelerated, statistics-based method for ULP pulsar detection and localisation. FITrig includes two complementary approaches -- an image domain and an image-frequency domain strategy. FITrig offers advantages by increasing sensitivity to faint pulsars, suppressing false positives (from noise, processing artefacts, or steady sources), and improving search efficiency in large-scale wide-field images. Compared to the state-of-the-art source finder SOFIA 2, FITrig increases the detection speed by 4.3 times for large images ($50\mathrm{K} \times 50\mathrm{K}$ pixels) and reduces false positives by up to 858.8 times (at 6$σ$ significance) for the image domain branch, while the image-frequency domain branch suppresses false positives even further. FITrig maintains the capability to detect pulsars that are 20 times fainter than surrounding steady features, even under critical Nyquist sampling conditions. In this article, the performance of FITrig is demonstrated using both real-world data (MeerKAT observations of PSR J0901-4046) and simulated datasets based on MeerKAT and SKA Array Assembly (AA) 2 telescope configurations. With its real-time processing capabilities and scalability, FITrig is a promising tool for next-generation telescopes, such as the SKA, with the potential to uncover hidden ULP pulsars.

Figures (26)

• Figure 1: Schematic representation of an image-based radio transient detection workflow, where the highlighted "Detection" component indicates the primary focus of this article.
• Figure 3: Three-snapshot unit in the detection model. These images are reconstructed from a simulated dataset generated by OSKAR using the VLA D telescope layout. Suppose the index of the top-left tile is (1,1). In this example, the pulsar is primarily located in tile (11,11). The colour bar indicates the intensity scales, which are normalised in this example for illustration purposes. In the right figure, the yellow-shadowed tile indicates the tile selected by tLISI, which will be passed to the next step for further localisation.
• Figure 4: An example of tiles in a difference image showing the side lobe effect of dirty beam: tile (a), which contains no pulsar, shows a larger sum of intensities due to the side lobes of the dirty beam convolved with the pulsar, compared to tile (b), which does contain a pulsar. This example is simulated using the VLA telescope layout.
• Figure 7: Diagram of FITrig: image domain detection approach. Here, the current state-of-the-art source finder, SOFIA 2, is used as an example to demonstrate the functionality of FITrig, though it could be replaced by other source finders.
• Figure 8: Diagram of FITrig: image-frequency domain detection approach.