BASSET: Bandpass-adaptive Single-pulse Search Toolkit—Optimized Subband Pulse Search Strategies for Faint Narrowband Fast Radio Bursts

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Abstract The existing single-pulse search algorithms for fast radio bursts (FRBs) do not adequately consider the frequency bandpass pattern of the pulse, rendering them incomplete for the relatively narrow-spectrum detection of pulses. We present a new search algorithm for narrowband pulses to update the existing standard pipeline, Bandpass-Adaptive Single-pulse SEarch Toolkit (BASSET). The BASSET algorithm employs a time–frequency correlation analysis to identify and remove the noise involved by the nondetection frequency band, thereby enhancing the signal-to-noise ratio (SNR) of the pulses. The BASSET algorithm was applied to the FAST real data set of FRB 20190520B, resulting in the discovery of additional 79 pulses through reprocessing. The new detection doubles the number of pulses compared to the previously known 75 pulses, bringing the total number of pulses to 154. In conjunction with the pulse calibration and the Markov Chain Monte Carlo simulated injection experiments, this work updates the quantified parameter space of the detection rate. Moreover, a parallel-accelerated version of the BASSET code was provided and evaluated through simulation. BASSET has the capacity of enhancing the detection sensitivity and the SNR of the narrowband pulses from the existing pipeline, offering high performance and flexible applicability. BASSET not only enhances the completeness of the low-energy narrowband pulse detection in a more robust mode, but also has the potential to further elucidate the FRB luminosity function at a wider energy scale.

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