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SPARKESX: Single-dish PARKES data sets for finding the uneXpected - Part 4

Commonwealth Scientific and Industrial Research Organisation
Yong, SukYee ; Hobbs, George ; Huynh, Minh ; Rolland, Vivien ; Petersson, Lars ; Norris, Ray ; Dai, Shi ; Luo, Rui ; Zic, Andrew
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/2jh1-3x70&rft.title=SPARKESX: Single-dish PARKES data sets for finding the uneXpected - Part 4&rft.identifier=https://doi.org/10.25919/2jh1-3x70&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=We present the Single-dish PARKES data sets for finding the uneXpected (SPARKESX), a compilation of real and simulated high-time resolution observations. SPARKESX comprises three mock surveys from the Parkes ''Murriyang'' radio telescope. A broad selection of simulated and injected expected signals (such as pulsars, fast radio bursts), poorly known signals (such as the features expected from flare stars) and unknown unknowns are generated for each survey. We provide a baseline by presenting how successful a typical pipeline based on the standard pulsar search software, PRESTO, is at finding the injected signals.\n\nThe dataset is designed to aid in the development of new search algorithms, including image processing, machine learning, and deep learning. The raw data, ground truth labels, and baseline are provided.\n\nThe collection is split into 4 parts. See collections in related links.\nPart 1 - Ground truth labels, injected images, multibeam dataset\nPart 2 - PAF dataset\nPart 3 - PAF dataset\nPart 4 - PAF dataset\n\nPublication: SPARKESX: Single-dish PARKES data sets for finding the uneXpected - A data challenge (Yong et a. 2022, submitted)\nLineage: The injected signals and simulated data were created using CSIRO's open source simulateSearch software.\nThe real data from the multibeam survey were acquired from the CSIRO Data Access Portal.&rft.creator=Yong, SukYee &rft.creator=Hobbs, George &rft.creator=Huynh, Minh &rft.creator=Rolland, Vivien &rft.creator=Petersson, Lars &rft.creator=Norris, Ray &rft.creator=Dai, Shi &rft.creator=Luo, Rui &rft.creator=Zic, Andrew &rft.date=2022&rft.edition=v3&rft_rights=Creative Commons Attribution 4.0 International Licence https://creativecommons.org/licenses/by/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2022.&rft_subject=simulation&rft_subject=extraterrestrial intelligence&rft_subject=transients&rft_subject=pulsars&rft_subject=fast radio bursts&rft_subject=flare stars&rft_subject=Astronomical sciences not elsewhere classified&rft_subject=Astronomical sciences&rft_subject=PHYSICAL SCIENCES&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution 4.0 International Licence
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Data is accessible online and may be reused in accordance with licence conditions

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Brief description

We present the Single-dish PARKES data sets for finding the uneXpected (SPARKESX), a compilation of real and simulated high-time resolution observations. SPARKESX comprises three mock surveys from the Parkes ''Murriyang'' radio telescope. A broad selection of simulated and injected expected signals (such as pulsars, fast radio bursts), poorly known signals (such as the features expected from flare stars) and unknown unknowns are generated for each survey. We provide a baseline by presenting how successful a typical pipeline based on the standard pulsar search software, PRESTO, is at finding the injected signals.

The dataset is designed to aid in the development of new search algorithms, including image processing, machine learning, and deep learning. The raw data, ground truth labels, and baseline are provided.

The collection is split into 4 parts. See collections in related links.
Part 1 - Ground truth labels, injected images, multibeam dataset
Part 2 - PAF dataset
Part 3 - PAF dataset
Part 4 - PAF dataset

Publication: SPARKESX: Single-dish PARKES data sets for finding the uneXpected - A data challenge (Yong et a. 2022, submitted)
Lineage: The injected signals and simulated data were created using CSIRO's open source simulateSearch software.
The real data from the multibeam survey were acquired from the CSIRO Data Access Portal.

Available: 2022-08-30

This dataset is part of a larger collection

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