Radio Galaxy Zoo: machine learning for radio source host galaxy cross-identification
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Alger, Matthew; Banfield, Julie; Ong, Cheng Soon; Rudnick, L.; Wong, O. Ivy; Wolf, Christian; Andernach, H.; Norris, Ray P.; Shabala, Stanislav S.
Description
We consider the problem of determining the host galaxies of radio sources by crossidentification. This has traditionally been done manually, which will be intractable for widearea radio surveys like the Evolutionary Map of the Universe. Automated cross-identification will be critical for these future surveys, and machine learning may provide the tools to develop such methods. We apply a standard approach from computer vision to cross-identification, introducing one possible way of automating...[Show more]
Collections | ANU Research Publications |
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Date published: | 2018 |
Type: | Journal article |
URI: | http://hdl.handle.net/1885/197953 |
Source: | Monthly Notices of the Royal Astronomical Society |
DOI: | 10.1093/mnras/sty1308 |
Access Rights: | Open Access |
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File | Description | Size | Format | Image |
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01_Alger_Radio_Galaxy_Zoo%3A_machine_2018.pdf | 3.68 MB | Adobe PDF |
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