Single-pulse classifier for the LOFAR Tied-Array All-sky Survey

D Michilli, J W T Hessels, Robert Lyon, Chia Min Tan, C Bassa, Sally Cooper, V I Kondratiev, Sotirios Sanidas, Benjamin Stappers, J van Leeuwen

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    Abstract

    Searches for millisecond-duration, dispersed single pulses have become a standard tool used during radio pulsar surveys in the last decade. They have enabled the discovery of two new classes of sources: rotating radio transients and fast radio bursts. However, we are now in a regime where the sensitivity to single pulses in radio surveys is often limited more by the strong background of radio frequency interference (RFI, which can greatly increase the false-positive rate) than by the sensitivity of the telescope itself. To mitigate this problem, we introduce the Single-pulse Searcher (SpS). This is a new machine-learning classifier designed to identify astrophysical signals in a strong RFI environment, and optimized to process the large data volumes produced by the new generation of aperture array telescopes. It has been specifically developed for
    the LOFAR Tied-Array All-Sky Survey (LOTAAS), an ongoing survey for pulsars
    and fast radio transients in the northern hemisphere. During its development, SpS discovered 7 new pulsars and blindly identified 80 known sources. The modular design of the software offers the possibility to easily adapt it to other studies with different instruments and characteristics. Indeed, SpS has already been used in other projects, e.g. to identify pulses from the fast radio burst source FRB 121102. The software development is complete and SpS is now being used to re-process all LOTAAS data collected to date.
    Original languageEnglish
    Pages (from-to)3457-3467
    Number of pages10
    JournalMonthly Notices of the Royal Astronomical Society
    Volume480
    Issue number3
    Early online date3 Aug 2018
    DOIs
    Publication statusPublished - 1 Nov 2018

    Keywords

    • pulsars: general
    • Surveys
    • Methods: Data analysis
    • Methods: statistical

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