Author
J. M. Simpson
Bio: J. M. Simpson is an academic researcher from Academia Sinica. The author has contributed to research in topics: Interstellar medium & Photometric redshift. The author has an hindex of 3, co-authored 3 publications receiving 164 citations.
Topics: Interstellar medium, Photometric redshift, Redshift, Galaxy
Papers
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Durham University1, University of Hertfordshire2, Academia Sinica3, Purple Mountain Observatory4, University of Nottingham5, University of Edinburgh6, European Southern Observatory7, University of Leicester8, Dalhousie University9, Australian National University10, University of Hawaii11, Leiden University12, Colby College13, Adam Mickiewicz University in Poznań14, National Autonomous University of Mexico15, University of British Columbia16, University of Manchester17, Lancaster University18, Max Planck Society19
TL;DR: In this paper, the authors present a full catalogue of MNRAS articles and their full catalogue will be made publicly available on acceptance of paper acceptance of the paper, and comments are welcome.
Abstract: Submitted to MNRAS; Comments welcome. Full catalogue will be made publicly available on acceptance of paper
95 citations
TL;DR: In this paper, an author-created, un-copyedited version of an article published in The Astrophysical Journal is presented, which is available online at https://doi.org/10.3847/1538-4357/aabe8c.
Abstract: This is an author-created, un-copyedited version of an article published in The Astrophysical Journal. The Version of Record is available online at https://doi.org/10.3847/1538-4357/aabe8c.
81 citations
Chinese Academy of Sciences1, Durham University2, University of Nottingham3, European Southern Observatory4, University of Edinburgh5, Academia Sinica6, University of Hertfordshire7, University of British Columbia8, Virginia Tech9, University of Hawaii at Manoa10, University of Leicester11, Adam Mickiewicz University in Poznań12, Dalhousie University13
TL;DR: In this paper, a combined radio + machine learning method is proposed to identify the likely multiwavelength counterparts to submillimeter sources detected in panoramic, single-dish submillimeters surveys.
Abstract: We describe the application of supervised machine-learning algorithms to identify the likely multiwavelength counterparts to submillimeter sources detected in panoramic, single-dish submillimeter surveys. As a training set, we employ a sample of 695 (S 870μm gsim 1 mJy) submillimeter galaxies (SMGs) with precise identifications from the ALMA follow-up of the SCUBA-2 Cosmology Legacy Survey's UKIDSS-UDS field (AS2UDS). We show that radio emission, near-/mid-infrared colors, photometric redshift, and absolute H-band magnitude are effective predictors that can distinguish SMGs from submillimeter-faint field galaxies. Our combined radio + machine-learning method is able to successfully recover ~85% of ALMA-identified SMGs that are detected in at least three bands from the ultraviolet to radio. We confirm the robustness of our method by dividing our training set into independent subsets and using these for training and testing, respectively, as well as applying our method to an independent sample of ~100 ALMA-identified SMGs from the ALMA/LABOCA ECDF-South Survey (ALESS). To further test our methodology, we stack the 870 μm ALMA maps at the positions of those K-band galaxies that are classified as SMG counterparts by the machine learning but do not have a >4.3σ ALMA detection. The median peak flux density of these galaxies is S 870μm = (0.61 ± 0.03) mJy, demonstrating that our method can recover faint and/or diffuse SMGs even when they are below the detection threshold of our ALMA observations. In future, we will apply this method to samples drawn from panoramic single-dish submillimeter surveys that currently lack interferometric follow-up observations to address science questions that can only be tackled with large statistical samples of SMGs.
28 citations
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TL;DR: In this article, the authors derive photometrically estimated redshifts for HDF galaxies with J 2 and bridge the redshift gap between those two samples, consistent with the predictions of Pei and Fall (1995) based on the evolving HI content of Lyman-alpha QSO absorption line systems.
Abstract: The Hubble Deep Field (HDF) is the deepest set of multicolor optical photometric observations ever undertaken, and offers a valuable data set with which to study galaxy evolution. Combining the optical WFPC2 data with ground-based near-infrared photometry, we derive photometrically estimated redshifts for HDF galaxies with J 2, and bridge the redshift gap between those two samples. The overall star formation or metal enrichment rate history is consistent with the predictions of Pei and Fall (1995) based on the evolving HI content of Lyman-alpha QSO absorption line systems.
310 citations
18 Jan 2012
TL;DR: In this paper, the authors used the large samples of luminous AGN and high red-redshift star-forming galaxies in COSMOS to redefine the AGN selection criteria for use in deep IRAC surveys.
Abstract: Spitzer IRAC selection is a powerful tool for identifying luminous AGN. For deep IRAC data, however, the AGN selection wedges currently in use are heavily contaminated by star-forming galaxies, especially at high redshift. Using the large samples of luminous AGN and high-redshift star-forming galaxies in COSMOS, we redefine the AGN selection criteria for use in deep IRAC surveys. The new IRAC criteria are designed to be both highly complete and reliable, and incorporate the best aspects of the current AGN selection wedges and of infrared power-law selection while excluding high redshift star-forming galaxies selected via the BzK, DRG, LBG, and SMG criteria. At QSO-luminosities of log L(2-10 keV) (ergs/s) > 44, the new IRAC criteria recover 75% of the hard X-ray and IRAC-detected XMM-COSMOS sample, yet only 38% of the IRAC AGN candidates have X-ray counterparts, a fraction that rises to 52% in regions with Chandra exposures of 50-160 ks. X-ray stacking of the individually X-ray non-detected AGN candidates leads to a hard X-ray signal indicative of heavily obscured to mildly Compton-thick obscuration (log N_H (cm^-2) = 23.5 +/- 0.4). While IRAC selection recovers a substantial fraction of luminous unobscured and obscured AGN, it is incomplete to low-luminosity and host-dominated AGN.
262 citations
Durham University1, University of Nottingham2, University of Western Australia3, Australian National University4, University of the Western Cape5, University of Leicester6, Dalhousie University7, European Southern Observatory8, University of Hertfordshire9, University of Edinburgh10, University of Hawaii11, University College London12, Leiden University13, University of British Columbia14, University of Manchester15, Max Planck Society16, Lancaster University17
TL;DR: In this paper, the physical properties of a large, homogeneously selected sample of ALMA-located sub-mm galaxies (SMGs) detected in the SCUBA-2 CLS 850-$\mu$m map of the UKIDSS/UDS field were analyzed.
Abstract: We analyse the physical properties of a large, homogeneously selected sample of ALMA-located sub-mm galaxies (SMGs) detected in the SCUBA-2 CLS 850-$\mu$m map of the UKIDSS/UDS field. This survey, AS2UDS, identified 707 SMGs across the ~1 sq.deg. field, including ~17 per cent which are undetected in the optical/near-infrared to $K$>~25.7 mag. We interpret the UV-to-radio data using a physically motivated model, MAGPHYS and determine a median photometric redshift of z=2.61+-0.08, with a 68th percentile range of z=1.8-3.4 and just ~6 per cent at z>4. The redshift distribution is well fit by a model combining evolution of the gas fraction in halos with the growth of halo mass past a threshold of ~4x10$^{12}$M$_\odot$, thus SMGs may represent the highly efficient collapse of gas-rich massive halos. Our survey provides a sample of the most massive, dusty galaxies at z>~1, with median dust and stellar masses of $M_d$=(6.8+-0.3)x10$^{8}$M$_\odot$ (thus, gas masses of ~10$^{11}$M$_\odot$) and $M_\ast=$(1.26+-0.05)x10$^{11}$M$_\odot$. These galaxies have gas fractions of $f_{gas}=$0.41+-0.02 with depletion timescales of ~150Myr. The gas mass function evolution at high masses is consistent with constraints at lower masses from blind CO-surveys, with an increase to z~2-3 and then a decline at higher redshifts. The space density and masses of SMGs suggests that almost all galaxies with $M_\ast$>~2x10$^{11}$M$_\odot$ have passed through an SMG-like phase. We find no evolution in dust temperature at a constant far-infrared luminosity across z~1.5-4. We show that SMGs appear to behave as simple homologous systems in the far-infrared, having properties consistent with a centrally illuminated starburst. Our study provides strong support for an evolutionary link between the active, gas-rich SMG population at z>1 and the formation of massive, bulge-dominated galaxies across the history of the Universe.
144 citations
TL;DR: The main advances ALMA has helped bring about in understanding of the dust and gas properties of high-redshift (z≳1) star-forming galaxies during these first 9 years of its science operations are reviewed, and the interesting questions that may be answered by ALMA in the years to come are highlighted.
Abstract: The Atacama Large Millimetre/submillimetre Array (ALMA) is currently in the process of transforming our view of star-forming galaxies in the distant (z≳1) universe. Before ALMA, most of what we kne...
116 citations
Durham University1, University of Hertfordshire2, Academia Sinica3, Purple Mountain Observatory4, University of Nottingham5, University of Edinburgh6, European Southern Observatory7, University of Leicester8, Dalhousie University9, Australian National University10, University of Hawaii11, Leiden University12, Colby College13, Adam Mickiewicz University in Poznań14, National Autonomous University of Mexico15, University of British Columbia16, University of Manchester17, Lancaster University18, Max Planck Society19
TL;DR: In this paper, the authors present a full catalogue of MNRAS articles and their full catalogue will be made publicly available on acceptance of paper acceptance of the paper, and comments are welcome.
Abstract: Submitted to MNRAS; Comments welcome. Full catalogue will be made publicly available on acceptance of paper
95 citations