Selection of radio pulsar candidates using artificial neural networks

Radio pulsar surveys are producing many more pulsar candidates than can be inspected by human experts in a practical length of time. Here we present a technique to automatically identify credible pulsar candidates from pulsar surveys using an artificial neural network. The technique has been applied...

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Bibliographic Details
Published in:Monthly notices of the Royal Astronomical Society 2010-10, Vol.407 (4), p.2443-2450
Main Authors: Eatough, R. P., Molkenthin, N., Kramer, M., Noutsos, A., Keith, M. J., Stappers, B. W., Lyne, A. G.
Format: Article
Language:English
Subjects:
Astronomy
Earth, ocean, space
Exact sciences and technology
methods: data analysis
Neural networks
Pulsars
pulsars: general
Radio astronomy
stars: neutron
Citations: Items that cite this one
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Summary:Radio pulsar surveys are producing many more pulsar candidates than can be inspected by human experts in a practical length of time. Here we present a technique to automatically identify credible pulsar candidates from pulsar surveys using an artificial neural network. The technique has been applied to candidates from a recent re-analysis of the Parkes multi-beam pulsar survey resulting in the discovery of a previously unidentified pulsar.
ISSN:0035-8711
1365-2966
DOI:10.1111/j.1365-2966.2010.17082.x