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    Rights statement: This is an author-created, un-copyedited version of an article accepted for publication/published in The Astrophysical Journal. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at doi:10.3847/1538-4357/ab4d53

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Multi-wavelength Properties of Radio- and Machine-learning-identified Counterparts to Submillimeter Sources in S2COSMOS

Research output: Contribution to journalJournal article

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  • Fang Xia An
  • J. M. Simpson
  • Ian Smail
  • A. M. Swinbank
  • Cong Ma
  • Daizhong Liu
  • P. Lang
  • E. Schinnerer
  • A. Karim
  • B. Magnelli
  • S. Leslie
  • F. Bertoldi
  • Chian-Chou Chen
  • J. E. Geach
  • Y. Matsuda
  • S. M. Stach
  • B. Gullberg
  • R. J. Ivison
  • Y. Ao
  • R. T. Coogan
  • A. P. Thomson
  • S. C. Chapman
  • R. Wang
  • Wei-Hao Wang
  • Y. Yang
  • R. Asquith
  • N. Bourne
  • K. Coppin
  • N. K. Hine
  • L. C. Ho
  • H. S. Hwang
  • Y. Kato
  • K. Lacaille
  • A. J. R. Lewis
  • I. Oteo
  • J. Scholtz
  • M. Sawicki
  • D. Smith
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Article number48
<mark>Journal publication date</mark>19/11/2019
<mark>Journal</mark>The Astrophysical Journal
Issue number1
Volume886
Number of pages18
Publication statusPublished
Original languageEnglish

Abstract

We identify multi-wavelength counterparts to 1147 submillimeter sourcesfrom the S2COSMOS SCUBA-2 survey of the COSMOS field by employing arecently developed radio+machine-learning method trained on a largesample of Atacama Large Millimeter/submillimeter Array(ALMA)–identified submillimeter galaxies (SMGs), including 260SMGs identified in the AS2COSMOS pilot survey. In total, we identify1222 optical/near-infrared (NIR)/radio counterparts to the 897 S2COSMOSsubmillimeter sources with S 850 > 1.6 mJy, yielding anoverall identification rate of (78 ± 9)%. We find that (22± 5)% of S2COSMOS sources have multiple identified counterparts.We estimate that roughly 27% of these multiple counterparts within thesame SCUBA-2 error circles very likely arise from physically associatedgalaxies rather than line-of-sight projections by chance. Thephotometric redshift of our radio+machine-learning-identified SMGsranges from z = 0.2 to 5.7 and peaks at z = 2.3 ± 0.1. The AGNfraction of our sample is (19 ± 4)%, which is consistent withthat of ALMA SMGs in the literature. Comparing with radio/NIR-detectedfield galaxy population in the COSMOS field, ourradio+machine-learning-identified counterparts of SMGs have the higheststar formation rates and stellar masses. These characteristics suggestthat our identified counterparts of S2COSMOS sources are arepresentative sample of SMGs at z ≲ 3. We employ ourmachine-learning technique to the whole COSMOS field and identified 6877potential SMGs, most of which are expected to have submillimeteremission fainter than the confusion limit of our S2COSMOS surveys({S}850μ {{m}}≲ 1.5 mJy). We study the clusteringproperties of SMGs based on this statistically large sample, findingthat they reside in high-mass dark matter halos ((1.2 ± 0.3)× 1013 h ‑1 {M}ȯ ),which suggests that SMGs may be the progenitors of massive ellipticalswe see in the local universe.

Bibliographic note

This is an author-created, un-copyedited version of an article accepted for publication/published in The Astrophysical Journal. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at doi:10.3847/1538-4357/ab4d53