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

An, Fang Xia and Simpson, J. M. and Smail, Ian and Swinbank, A. M. and Ma, Cong and Liu, Daizhong and Lang, P. and Schinnerer, E. and Karim, A. and Magnelli, B. and Leslie, S. and Bertoldi, F. and Chen, Chian-Chou and Geach, J. E. and Matsuda, Y. and Stach, S. M. and Wardlow, J. L. and Gullberg, B. and Ivison, R. J. and Ao, Y. and Coogan, R. T. and Thomson, A. P. and Chapman, S. C. and Wang, R. and Wang, Wei-Hao and Yang, Y. and Asquith, R. and Bourne, N. and Coppin, K. and Hine, N. K. and Ho, L. C. and Hwang, H. S. and Kato, Y. and Lacaille, K. and Lewis, A. J. R. and Oteo, I. and Scholtz, J. and Sawicki, M. and Smith, D. (2019) Multi-wavelength Properties of Radio- and Machine-learning-identified Counterparts to Submillimeter Sources in S2COSMOS. The Astrophysical Journal, 886 (1): 48. ISSN 0004-637X

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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.