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dc.contributor.authorLee, K
dc.contributor.authorStovall, K
dc.contributor.authorJenet, F
dc.contributor.authorMartinez, J
dc.contributor.authorDartez, L
dc.contributor.authorMata, A
dc.contributor.authorLunsford, G
dc.contributor.authorCohen, S
dc.contributor.authorBiwer, C
dc.contributor.authorRohr, M
dc.identifier.citationLee, K and Stovall, K and Jenet, F and Martinez, J and Dartez, L and Mata, A and Lunsford, G and Cohen, S and Biwer, C and Rohr, M and Flanigan, J and Walker, A and Banaszak, S and Allen, B and Barr, E and Bhat, N. d. and Bogdanova, S and Brazier, A and Camilo, F and Champion, D and Cordes, J and Crawford, F. and Deneva, J and Desvignes, G and Ferdman, R and Freire, P and Hessels, J and Karuppusamy, R and Kaspi, V and Knispel, B and Kramer, M and Lazarus, P and Lynch, R and Lyne, A. and McLaughlin, M and Ransom, Scott and Scholz, P and Siemens, X and Spitler, L and Stairs, I and Tan, M and van Leeuwen, Joeri and Zhu, W. 2013. PEACE: pulsar evaluation algorithm for candidate extraction - a software package for post-analysis processing of pulsar survey candidates. Monthly Notices of the Royal Astronomical Society. 433 (1): pp. 688-694.

Modern radio pulsar surveys produce a large volume of prospective candidates, the majority of which are polluted by human-created radio frequency interference or other forms of noise. Typically, large numbers of candidates need to be visually inspected in order to determine if they are real pulsars. This process can be labour intensive. In this paper, we introduce an algorithm called Pulsar Evaluation Algorithm for Candidate Extraction (peace) which improves the efficiency of identifying pulsar signals. The algorithm ranks the candidates based on a score function. Unlike popular machine-learning-based algorithms, no prior training data sets are required. This algorithm has been applied to data from several large-scale radio pulsar surveys. Using the human-based ranking results generated by students in the Arecibo Remote Command Center programme, the statistical performance of peace was evaluated. It was found that peace ranked 68?per?cent of the student-identified pulsars within the top 0.17?per?cent of sorted candidates, 95?per?cent within the top 0.34?per?cent and 100?per?cent within the top 3.7?per?cent. This clearly demonstrates that peace significantly increases the pulsar identification rate by a factor of about 50 to 1000. To date, peace has been directly responsible for the discovery of 47 new pulsars, 5 of which are millisecond pulsars that may be useful for pulsar timing based gravitational-wave detection projects

dc.publisherWiley-Blackwell Publishing Ltd.
dc.subjectpulsars: general
dc.subjectmethods: statistical
dc.titlePEACE: pulsar evaluation algorithm for candidate extraction - a software package for post-analysis processing of pulsar survey candidates
dc.typeJournal Article
dcterms.source.titleRoyal Astronomical Society. Monthly Notices
curtin.accessStatusOpen access via publisher

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