Data

Parkes observations for project P1072 semester 2020OCTS_02

The University of Western Australia
Hobbs, George ; Dawson, Joanne ; Norris, Ray ; Wong, O. Ivy ; Huynh, Minh ; Li, Di ; Galvin, Tim ; Dai, Shi ; Wang, Chen ; Zhang, Songbo ; Zhu, Weiwei ; Farajollahi, Hossein ; Luo, Rui ; Wang, Rosalind ; Petersson, Lars ; Rolland, Vivien
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/b7xb-zz51&rft.title=Parkes observations for project P1072 semester 2020OCTS_02&rft.identifier=10.25919/b7xb-zz51&rft.publisher=CSIRO Publishing&rft.description=The Parkes telescope has been used to discover more than half of the known pulsars. The techniques used continue to be optimised, but the basic search strategy has not changed in decades. In particular the algorithms produce more candidates than can be searched by eye and so machine learning algorithms are used to sift through the candidates. However, the properties of the candidates were designed for human viewing. Here we propose to record data streams from the highly-versatile Parkes UWL system in order to develop pulsar search algorithms that have been developed, from the ground-up, explicitly for machine learning algorithms.&rft.creator=Hobbs, George &rft.creator=Dawson, Joanne &rft.creator=Norris, Ray &rft.creator=Wong, O. Ivy &rft.creator=Huynh, Minh &rft.creator=Li, Di &rft.creator=Galvin, Tim &rft.creator=Dai, Shi &rft.creator=Wang, Chen &rft.creator=Zhang, Songbo &rft.creator=Zhu, Weiwei &rft.creator=Farajollahi, Hossein &rft.creator=Luo, Rui &rft.creator=Wang, Rosalind &rft.creator=Petersson, Lars &rft.creator=Rolland, Vivien &rft.date=2021&rft.type=dataset&rft.language=English Access the data
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The Parkes telescope has been used to discover more than half of the known pulsars. The techniques used continue to be optimised, but the basic search strategy has not changed in decades. In particular the algorithms produce more candidates than can be searched by eye and so machine learning algorithms are used to sift through the candidates. However, the properties of the candidates were designed for human viewing. Here we propose to record data streams from the highly-versatile Parkes UWL system in order to develop pulsar search algorithms that have been developed, from the ground-up, explicitly for machine learning algorithms.

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Associated Persons
Di Li (Creator); Chen Wang (Creator); Songbo Zhang (Creator)George Hobbs (Creator); Joanne Dawson (Creator); Ray Norris (Creator); Tim Galvin (Creator); Shi Dai (Creator); Weiwei Zhu (Creator); Hossein Farajollahi (Creator); Rui Luo (Creator); Rosalind Wang (Creator); Lars Petersson (Creator); Vivien Rolland (Creator)

Issued: 2021-04-08

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