Published June 1, 2020 | Version v1
Journal article

SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES). IV. Spatial Clustering and Halo Masses of Submillimeter Galaxies

  • 1. Academia Sinica Institute of Astronomy and Astrophysics (ASIAA), No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan (China)
  • 2. Centre for Extragalactic Astronomy, Department of Physics, Durham University, South Road, Durham, DH1 3LE (United Kingdom)
  • 3. Department of Physics & Astronomy, University of British Columbia, BC (Canada)
  • 4. Purple Mountain Observatory and Key Laboratory for Radio Astronomy, Chinese Academy of Sciences, Nanjing 210033 (China)
  • 5. Department of Physics and Astronomy, University of Victoria, Elliott Building, 3800 Finnerty Road, Victoria, BC V8P 5C2 (Canada)
  • 6. Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX13RH (United Kingdom)
  • 7. Department of Physics and Astronomy, University of British Columbia, 6225 Agricultural Road, Vancouver, BC, V6T 1Z1 (Canada)
  • 8. Department of Physics, Blackett Lab, Imperial College, Prince Consort Road, London, SW7 2AZ (United Kingdom)
  • 9. University of Nottingham, School of Physics & Astronomy, Nottingham, NG7 2RD (United Kingdom)
  • 10. Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT (United Kingdom)
  • 11. Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871 (China)
  • 12. Natural Science Research Institute, University of Seoul, 163 Seoulsiripdaero, Dongdaemun-gu, Seoul 02504 (Korea, Republic of)
  • 13. Korea Astronomy and Space Science Institute, 776 Daedeokdae-ro, Yuseong-gu, Daejeon 34055 (Korea, Republic of)

Description

We analyze an extremely deep 450 μm image (1σ = 0.56 mJy beam−1) of a ≃300 arcmin2 area in the CANDELS/COSMOS field as part of the Sub-millimeter Common User Bolometric Array-2 Ultra Deep Imaging EAO Survey. We select a robust (signal-to-noise ratio ≥4) and flux-limited (≥4 mJy) sample of 164 submillimeter galaxies (SMGs) at 450 μm that have K-band counterparts in the COSMOS2015 catalog identified from radio or mid-infrared imaging. Utilizing this SMG sample and the 4705 K-band-selected non-SMGs that reside within the noise level ≤1 mJy beam−1 region of the 450 μm image as a training set, we develop a machine-learning classifier using K-band magnitude and color–color pairs based on the 13-band photometry available in this field. We apply the trained machine-learning classifier to the wider COSMOS field (1.6 deg2) using the same COSMOS2015 catalog and identify a sample of 6182 SMG candidates with similar colors. The number density, radio and/or mid-infrared detection rates, redshift and stellar-mass distributions, and the stacked 450 μm fluxes of these SMG candidates, from the S2COSMOS observations of the wide field, agree with the measurements made in the much smaller CANDELS field, supporting the effectiveness of the classifier. Using this SMG candidate sample, we measure the two-point autocorrelation functions from z = 3 down to z = 0.5. We find that the SMG candidates reside in halos with masses of ≃(2.0 ± 0.5) × 1013 h −1 M across this redshift range. We do not find evidence of downsizing that has been suggested by other recent observational studies.

Availability note (English)

Available from http://dx.doi.org/10.3847/1538-4357/ab8eaf

Additional details

Identifiers

Publishing Information

Journal Title
Astrophysical Journal
Journal Volume
895
Journal Issue
2
Journal Page Range
[18 p.]
ISSN
0004-637X
CODEN
ASJOAB

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52065147
Subject category
S79: ASTROPHYSICS, COSMOLOGY AND ASTRONOMY;
Descriptors DEI
BOLOMETERS; DENSITY; GALAXIES; MACHINE LEARNING; MASS; MASS DISTRIBUTION; PHOTOMETRY; RED SHIFT; UNIVERSE
Descriptors DEC
ALGORITHMS; ARTIFICIAL INTELLIGENCE; DISTRIBUTION; LEARNING; MATHEMATICAL LOGIC; MEASURING INSTRUMENTS; PHYSICAL PROPERTIES; SPATIAL DISTRIBUTION