Automated Cross-identifying Radio to Infra-red Surveys Using the LRPY Algorithm: A Case Study

Simple item page
aut.relation.journalMonthly Notices of the Royal Astronomical Societyen_NZ
aut.researcherWeston, Stuart
dc.contributor.authorWeston, Sen_NZ
dc.contributor.authorSeymour, Nen_NZ
dc.contributor.authorGulyaev, Sen_NZ
dc.contributor.authorNorris, RPen_NZ
dc.contributor.authorBanfield, Jen_NZ
dc.contributor.authorVaccari, Men_NZ
dc.contributor.authorHopkins, AMen_NZ
dc.contributor.authorFranzen, TMOen_NZ
dc.date.accessioned2019-07-30T02:44:38Z
dc.date.available2019-07-30T02:44:38Z
dc.date.copyright2017-10-04en_NZ
dc.date.issued2017-10-04en_NZ
dc.description.abstractCross-identifying complex radio sources with optical or infra red (IR) counterparts in surveys such as the Australia Telescope Large Area Survey (ATLAS) has tradi- tionally been performed manually. However, with new surveys from the Australian Square Kilometre Array Path nder (ASKAP) detecting many tens of million of ra- dio sources such an approach is no longer feasible. This paper presents new software (LRPY - Likelihood Ratio in PYthon) to automate the process of cross-identifying radio sources with catalogues at other wavelengths. LRPY implements the Likelihood Ratio (LR) technique with a modi cation to account for two galaxies contributing to a sole measured radio component. We demonstrate LRPY by applying it to ATLAS DR3 and a Spitzer-based multi-wavelength fusion catalogue, identifying 3,848 matched sources via our LR-based selection criteria. A subset of 1987 sources have ux density values for all IRAC bands which allow us to use criteria to distinguish between active galactic nuclei (AGN) and star-forming galaxies (SFG). We nd that 936 radio sources ( 47 %) meet both of the Lacy and Stern AGN selection criteria. Of the matched sources, 295 have spectroscopic redshifts and we examine the radio to IR ux ratio vs redshift, proposing an AGN selection criterion below the Elvis radio-loud (RL) AGN limit for this dataset. Taking the union of all three AGN selection criteria we identify 956 as AGN ( 48 %). From this dataset, we nd a decreasing fraction of AGN with lower radio ux densities consistent with other results in the literature.en_NZ
dc.identifier.citationMonthly Notices of the Royal Astronomical Society, Volume 473, Issue 4, February 2018, Pages 4523–4537, https://doi.org/10.1093/mnras/stx2562
dc.identifier.doi10.1093/mnras/stx2562en_NZ
dc.identifier.issn0035-8711en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/12697
dc.publisherOxford University Press (OUP)en_NZ
dc.relation.urihttps://academic.oup.com/mnras/article/473/4/4523/4554395
dc.rightsThis article has been accepted for publication in Monthly Notices of the Royal Astronomical Society ©: 2018 S. D. Weston, N. Seymour, S. Gulyaev, R. P. Norris, J. Banfield, M. Vaccari, A. M. Hopkins, T. M. O. Franzen Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectMethods: data analysis, catalogues, surveys; Radio continuum: galaxies
dc.titleAutomated Cross-identifying Radio to Infra-red Surveys Using the LRPY Algorithm: A Case Studyen_NZ
dc.typeJournal Article
pubs.elements-id313990
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/Engineering, Computer & Mathematical Sciences
pubs.organisational-data/AUT/Design & Creative Technologies/Engineering, Computer & Mathematical Sciences/ISASR
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
MN-15-39174-MJ.pdf
Size:
17.3 MB
Format:
Adobe Portable Document Format
Description:
Journal article
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
AUT Grant of Licence for Scholarly Commons Feb2017.pdf
Size:
239.25 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau