The Northern High Time Resolution Universe pulsar survey -- II. Single-pulse search set-up and simulations
L. J. M. Houben, H. Falcke, L. G. Spitler, E. D. Barr, M. Berezina, D. J. Champion, R. Karuppusamy, M. Kramer
TL;DR
This work develops a dedicated single-pulse search pipeline for the HTRU-North data, augmented by FRBfaker for synthetic SP injections and RFIbye for radio-frequency interference mitigation. Through extensive injection-recovery tests across four FRB morphologies, it quantifies pipeline completeness (roughly $\mathrm{S/N} \approx 11$ for 95% recall) and a fluence sensitivity near $0.16~\mathrm{Jy\,ms}$, while also evaluating the impact of propagation effects and the detector's boxcar discretization. The results demonstrate the pipeline's readiness to process the full HTRU-North dataset, reveal RFI characteristics at Effelsberg, and uncover eight SP trains plus 141 SP candidates that may indicate new neutron stars or FRB-like phenomena. The work also highlights limitations in current FETCH models and the need for morphology-aware retraining, offering concrete paths (training data via FRBfaker, sub-banded searches, padding) to improve detection of complex, Band-limited, or highly scattered SPs with practical implications for future FRB/pulsar surveys.
Abstract
The High Time Resolution Universe (HTRU) survey is an all-sky survey looking for pulsars and other radio transients. A new single-pulse (SP) search pipeline is presented, tailored to the northern part of the HTRU survey collected with the 100m Effelsberg Radio Telescope. In a selection of this data, synthetic SPs are injected with frequency-time structures resembling those of the detected Fast Radio Burst (FRB) population and processed by the pipeline to characterize its performance. Therefore, several new software toolkits have been developed (FRBfaker and RFIbye) to enable the injection of SPs with complex frequency-time structures and cope with the Radio Frequency Interference (RFI) in the survey's data. The operation of these toolkits is described alongside the overall functionality of the SP pipeline. Qualification of the pipeline confirmed that it is ready to process all the HTRU-North data. Additionally, the survey's sensitivity to SPs, the impact of RFI thereon, the performance of the deep-learning classifier FETCH, and some insights that may be used to improve the pipeline's performance in the future are determined. Within the small data sample analysed, 21 known pulsars and a RRAT are detected. In addition, eight faint SP trains that might originate from yet undiscovered neutron stars and 141 isolated SP candidates were discovered.
