The High Time Resolution Universe Pulsar Survey-XIX. A coherent GPU accelerated reprocessing and the discovery of 71 pulsars in the Southern Galactic plane
R. Sengar, M. Bailes, V. Balakrishnan, E. D. Barr, N. D. R. Bhat, M., Burgay, M. C. i Bernadich, A. D. Cameron, D. J. Champion, W. Chen, C. M. L., Flynn, A. Jameson, S. Johnston, M. J. Keith, M. Kramer, V. Morello, C. Ng, A., Possenti, S. Stevenson, R. M. Shannon, W. van Straten

TL;DR
This paper presents a GPU-accelerated reprocessing of the HTRU-S LowLat pulsar survey data, leading to the discovery of 71 new pulsars, including millisecond and high-DM pulsars, by employing advanced coherent search techniques.
Contribution
The study introduces a GPU-accelerated, coherent reprocessing pipeline that enhances pulsar detection sensitivity and discovers new pulsars missed by previous analyses.
Findings
Discovered 71 new pulsars, including 6 MSPs and 7 high-DM pulsars.
Achieved survey detection goals and identified reasons for previous missed pulsars.
Demonstrated the effectiveness of coherent folding and candidate classification techniques.
Abstract
We have conducted a GPU accelerated reprocessing of of the archival data from the High Time Resolution Universe South Low Latitude (HTRU-S LowLat) pulsar survey by implementing a pulsar search pipeline that was previously used to reprocess the Parkes Multibeam pulsar survey (PMPS). We coherently searched the full 72-min observations of the survey with an acceleration search range up to , which is most sensitive to binary pulsars experiencing nearly constant acceleration during 72 minutes of their orbital period. Here we report the discovery of 71 pulsars, including 6 millisecond pulsars (MSPs) of which five are in binary systems, and seven pulsars with very high dispersion measures (DM ). These pulsar discoveries largely arose by folding candidates to a much lower spectral signal-to-noise ratio than previous surveys, and…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Distributed and Parallel Computing Systems · Parallel Computing and Optimization Techniques
