Radio Galaxy Zoo data release 1: 100185 radio source classifications from the FIRST and ATLAS surveys

ABSTRACT Radio galaxies can extend far beyond the stellar component of their originating host galaxies, and their radio emission can consist of multiple discrete components. Furthermore, the apparent source structure will depend on survey sensitivity, resolution and the observing frequency. Associated discrete radio components and their originating host galaxy are typically identified through a visual comparison of radio and mid-infrared survey images. We present the first data release of Radio Galaxy Zoo, an online citizen science project that enlists the help of citizen scientists to cross-match extended radio sources from the Faint Images of the Radio Sky at Twenty Centimeters (FIRST) and the Australia Telescope Large Area Survey (ATLAS) surveys, often with complex structure, to host galaxies in 3.6 $\mu$m infrared images from the Wide-field Infrared Survey Explorer (WISE) and the SpitzerSpace Telescope. This first data release consists of 100 185 classifications for 99 146 radio sources from the FIRST survey and 583 radio sources from the ATLAS survey. We include two tables for each of the FIRST and ATLAS surveys: (1) the identification of all components making up each radio source and (2) the cross-matched host galaxies. These classifications have an average reliability of 0.83 based on the weighted consensus levels of our citizen scientists. The reliability of the DR1 catalogue has been further demonstrated through several parallel studies which used the pre-release versions of this catalogue to train and prototype machine learning-based classifiers. We also include a brief description of the radio source populations catalogued by RGZ DR1.

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Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2024-12-23
DOI
https://doi.org/10.1093/mnras/stae2790
Citations
7
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
2.32

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article

Radio Galaxy Zoo data release 1: 100185 radio source classifications from the FIRST and ATLAS surveys

R. P. Norris, Avery Garon, Matthew J. Alger, H. Andernach et al.
7 citations
Monthly Notices of the Royal Astronomical Society
Galaxies: Formation, Evolution, Phenomena
2.32
article

Radio Galaxy Zoo data release 1: 100185 radio source classifications from the FIRST and ATLAS surveys

R. P. Norris, Avery Garon, Matthew J. Alger, H. Andernach, Julie Banfield, K. W. Willett, L. Rudnick, Hongming Tang, N. Seymour, Jesse G. Swan, S. V. White, A. D. Kapińska, Brooke Simmons, Stanislav S. Shabala, Chris Lintott, M. J. Hardcastle, Kevin Schawinski, O. Ivy Wong
article en
7 citations

Abstract

ABSTRACT Radio galaxies can extend far beyond the stellar component of their originating host galaxies, and their radio emission can consist of multiple discrete components. Furthermore, the apparent source structure will depend on survey sensitivity, resolution and the observing frequency. Associated discrete radio components and their originating host galaxy are typically identified through a visual comparison of radio and mid-infrared survey images. We present the first data release of Radio Galaxy Zoo, an online citizen science project that enlists the help of citizen scientists to cross-match extended radio sources from the Faint Images of the Radio Sky at Twenty Centimeters (FIRST) and the Australia Telescope Large Area Survey (ATLAS) surveys, often with complex structure, to host galaxies in 3.6 $\mu$m infrared images from the Wide-field Infrared Survey Explorer (WISE) and the SpitzerSpace Telescope. This first data release consists of 100 185 classifications for 99 146 radio sources from the FIRST survey and 583 radio sources from the ATLAS survey. We include two tables for each of the FIRST and ATLAS surveys: (1) the identification of all components making up each radio source and (2) the cross-matched host galaxies. These classifications have an average reliability of 0.83 based on the weighted consensus levels of our citizen scientists. The reliability of the DR1 catalogue has been further demonstrated through several parallel studies which used the pre-release versions of this catalogue to train and prototype machine learning-based classifiers. We also include a brief description of the radio source populations catalogued by RGZ DR1.

Monthly Notices of the Royal Astronomical SocietyVol. 536(4)
Australian National University (AU), Commonwealth Scientific and Industrial Research Organisation (AU), University of Tasmania (AU), Universidad de Guanajuato (MX), University of Minnesota (US), University of Hertfordshire (GB), The University of Western Australia (AU), Rhodes University (ZA), Curtin University (AU), National Radio Astronomy Observatory (US), University of Manchester (GB), ETH Zurich (CH), University of Oxford (GB), Institute of Particle Physics (CA), South African Radio Astronomy Observatory (ZA), Inspire (CH), Astronomy and Space (AU), Thüringer Landessternwarte Tautenburg (DE), International Centre for Radio Astronomy Research (AU), Data61 (AU), Western Sydney University (AU), Lancaster University (GB), Tsinghua University (CN)
National Science Foundation, National Aeronautics and Space Administration, California Institute of Technology, University of Minnesota, National Radio Astronomy Observatory, China Postdoctoral Science Foundation, Tsinghua University, Universidad de Guanajuato, Jet Propulsion Laboratory, University of California, Los Angeles, Science and Technology Facilities Council
Openalex Percentile: Top 12%
Galaxies: Formation, Evolution, Phenomena
2.32
DOIOpen Access PDFOpenAlex
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