Dr DAVID MALTBY's Outputs (3)

An ALMA survey of the SCUBA-2 CLS UDS field: Physical properties of 707 Sub-millimetre Galaxies (2020)
Journal Article
Dudzevičiūtė, U., Smail, I., Swinbank, A. M., Stach, S. M., Almaini, O., da Cunha, E., An, F. X., Arumugam, V., Birkin, J., Blain, A. W., Chapman, S. C., Chen, C.-C., Conselice, C. J., Coppin, K. E. K., Dunlop, J. S., Farrah, D., Geach, J. E., Gullberg, B., Hartley, W. G., Hodge, J. A., …van der Werf, P. (2020). An ALMA survey of the SCUBA-2 CLS UDS field: Physical properties of 707 Sub-millimetre Galaxies. Monthly Notices of the Royal Astronomical Society, 494(3), 3828–3860. https://doi.org/10.1093/mnras/staa769

Long-term NIR Variability in the UKIDSS Ultra Deep Survey: a new probe of AGN activity at high redshift (2020)
Journal Article
Elmer, E., Almaini, O., Merrifield, M., Hartley, W. G., Maltby, D. T., Lawrence, A., Botti, I., & Hirst, P. (2020). Long-term NIR Variability in the UKIDSS Ultra Deep Survey: a new probe of AGN activity at high redshift. Monthly Notices of the Royal Astronomical Society, 493(2), 3026-3035. https://doi.org/10.1093/mnras/staa381

We present the first attempt to select active galactic nuclei (AGN) using long-Term near-infrared (NIR) variability. By analysing the K-band light curves of all the galaxies in the UKIRT Infrared Deep Sky Survey (UKIDSS) Ultra Deep Survey, the deepes... Read More about Long-term NIR Variability in the UKIDSS Ultra Deep Survey: a new probe of AGN activity at high redshift.

A machine-learning method for identifying multiwavelength counterparts of submillimeter galaxies: training and testing using AS2UDS and ALESS (2018)
Journal Article
An, F. X., Stach, S., Smail, I., Swinbank, A., Almaini, O., Simpson, C., Hartley, W., Maltby, D., Ivison, R., Arumugam, V., Wardlow, J., Cooke, E., Gullberg, B., Thomson, A., Chen, C.-C., Simpson, J., Geach, J., Scott, D., Dunlop, J., Farrah, D., …Coppin, K. (2018). A machine-learning method for identifying multiwavelength counterparts of submillimeter galaxies: training and testing using AS2UDS and ALESS. Astrophysical Journal, 862(2), Article 101. https://doi.org/10.3847/1538-4357/aacdaa

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... Read More about A machine-learning method for identifying multiwavelength counterparts of submillimeter galaxies: training and testing using AS2UDS and ALESS.