Improved selection criteria for HII regions, based on IRAS sources
We present new criteria for selecting HII regions from the Infrared Astronomical Satellite (IRAS) Point Source Catalogue (PSC), based on an HII region catalogue derived manually from the all-sky Wide-field Infrared Survey Explorer (WISE). The criteria are used to augment the number of HII region can...
| Main Authors: | , , , , , , , , |
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| Format: | Journal Article |
| Published: |
Oxford University Press
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/71516 |
| _version_ | 1848762500894425088 |
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| author | Yan, Q. Xu, Y. Walsh, A. Macquart, Jean-Pierre MacLeod, G. Zhang, B. Hancock, Paul Chen, X. Tang, Z. |
| author_facet | Yan, Q. Xu, Y. Walsh, A. Macquart, Jean-Pierre MacLeod, G. Zhang, B. Hancock, Paul Chen, X. Tang, Z. |
| author_sort | Yan, Q. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | We present new criteria for selecting HII regions from the Infrared Astronomical Satellite (IRAS) Point Source Catalogue (PSC), based on an HII region catalogue derived manually from the all-sky Wide-field Infrared Survey Explorer (WISE). The criteria are used to augment the number of HII region candidates in theMilkyWay. The criteria are defined by the linear decision boundary of two samples: IRAS point sources associated with known HII regions, which serve as theHII region sample, and IRAS point sources at high Galactic latitudes, which serve as the non-H II region sample. Amachine learning classifier, specifically a support vector machine, is used to determine the decision boundary. We investigate all combinations of four IRAS bands and suggest that the optimal criterion is log (F60/F12) ? (-0.19 × log (F100/F25) + 1.52), with detections at 60 and 100 µm. This selects 3041 HII region candidates from the IRAS PSC. We find that IRAS HII region candidates show evidence of evolution on the two-colour diagram. Merging the WISE HII catalogue with IRAS HII region candidates, we estimate a lower limit of approximately 10 200 for the number of HII regions in the Milky Way. |
| first_indexed | 2025-11-14T10:48:34Z |
| format | Journal Article |
| id | curtin-20.500.11937-71516 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:48:34Z |
| publishDate | 2018 |
| publisher | Oxford University Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-715162019-02-14T07:18:56Z Improved selection criteria for HII regions, based on IRAS sources Yan, Q. Xu, Y. Walsh, A. Macquart, Jean-Pierre MacLeod, G. Zhang, B. Hancock, Paul Chen, X. Tang, Z. We present new criteria for selecting HII regions from the Infrared Astronomical Satellite (IRAS) Point Source Catalogue (PSC), based on an HII region catalogue derived manually from the all-sky Wide-field Infrared Survey Explorer (WISE). The criteria are used to augment the number of HII region candidates in theMilkyWay. The criteria are defined by the linear decision boundary of two samples: IRAS point sources associated with known HII regions, which serve as theHII region sample, and IRAS point sources at high Galactic latitudes, which serve as the non-H II region sample. Amachine learning classifier, specifically a support vector machine, is used to determine the decision boundary. We investigate all combinations of four IRAS bands and suggest that the optimal criterion is log (F60/F12) ? (-0.19 × log (F100/F25) + 1.52), with detections at 60 and 100 µm. This selects 3041 HII region candidates from the IRAS PSC. We find that IRAS HII region candidates show evidence of evolution on the two-colour diagram. Merging the WISE HII catalogue with IRAS HII region candidates, we estimate a lower limit of approximately 10 200 for the number of HII regions in the Milky Way. 2018 Journal Article http://hdl.handle.net/20.500.11937/71516 10.1093/MNRAS/STY518 Oxford University Press fulltext |
| spellingShingle | Yan, Q. Xu, Y. Walsh, A. Macquart, Jean-Pierre MacLeod, G. Zhang, B. Hancock, Paul Chen, X. Tang, Z. Improved selection criteria for HII regions, based on IRAS sources |
| title | Improved selection criteria for HII regions, based on IRAS sources |
| title_full | Improved selection criteria for HII regions, based on IRAS sources |
| title_fullStr | Improved selection criteria for HII regions, based on IRAS sources |
| title_full_unstemmed | Improved selection criteria for HII regions, based on IRAS sources |
| title_short | Improved selection criteria for HII regions, based on IRAS sources |
| title_sort | improved selection criteria for hii regions, based on iras sources |
| url | http://hdl.handle.net/20.500.11937/71516 |