Radial gradients in initial mass function sensitive absorption features in the Coma brightest cluster galaxies

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 465:1 (2017) 192-212

Authors:

S Zieleniewski, RCW Houghton, N Thatte, RL Davies, SP Vaughan

Evidence that the AGN dominates the radio emission in z ~ 1 radio-quiet quasars

Monthly Notices of the Royal Astronomical Society Oxford University Press 468:1 (2017) 217-238

Authors:

SV White, Matthew Jarvis, E Kalfountzou, MJ Hardcastle, A Verma, JM Cao Orjales, J Stevens

Abstract:

In order to understand the role of radio-quiet quasars (RQQs) in galaxy evolution, we must determine the relative levels of accretion and star-formation activity within these objects. Previous work at low radio flux densities has shown that accretion makes a significant contribution to the total radio emission, in contrast with other quasar studies that suggest star formation dominates. To investigate, we use 70 RQQs from the Spitzer-Herschel Active Galaxy Survey. These quasars are all at z ∼ 1, thereby minimizing evolutionary effects, and have been selected to span a factor of ∼100 in optical luminosity, so that the luminosity dependence of their properties can be studied. We have imaged the sample using the Karl G. Jansky Very Large Array (JVLA), whose high sensitivity results in 35 RQQs being detected above 2σ. This radio data set is combined with far-infrared luminosities derived from grey-body fitting to Herschel photometry. By exploiting the far-infrared-radio correlation observed for star-forming galaxies, and comparing two independent estimates of the star-formation rate, we show that star formation alone is not sufficient to explain the total radio emission. Considering RQQs above a 2σ detection level in both the radio and the far-infrared, 92 per cent are accretion dominated, and the accretion process accounts for 80 per cent of the radio luminosity when summed across the objects. The radio emission connected with accretion appears to be correlated with the optical luminosity of the RQQ, whilst a weaker luminosity dependence is evident for the radio emission connected with star formation.

Discovery of water at high spectral resolution in the atmosphere of 51 Peg b

(2017)

Authors:

JL Birkby, RJ de Kok, M Brogi, H Schwarz, IAG Snellen

THE SAMI GALAXY SURVEY: REVISITING GALAXY CLASSIFICATION THROUGH HIGH-ORDER STELLAR KINEMATICS

ASTROPHYSICAL JOURNAL 835:1 (2017) ARTN 104

Authors:

J van de Sande, J Bland-Hawthorn, LMR Fogarty, L Cortese, F d'Eugenio, SM Croom, N Scott, JT Allen, S Brough, JJ Bryant, G Cecil, M Colless, WJ Couch, R Davies, PJ Elahi, C Foster, G Goldstein, M Goodwin, B Groves, I-T Ho, H Jeong, DH Jones, IS Konstantopoulos, JS Lawrence, SK Leslie, AR Lopez-Sanchez, RM McDermid, R McElroy, AM Medling, S Oh, MS Owers, SN Richards, AL Schaefer, R Sharp, SM Sweet, D Taranu, C Tonini, CJ Walcher, SK Yi

A fast machine learning based algorithm for MKID readout power tuning

ISSTT 2017 - 28th International Symposium on Space Terahertz Technology 2017-March (2017)

Authors:

RH Dodkins, K O'Brien, N Thatte, S Mahashabde, N Fruitwala, S Meeker, A Walter, P Szypryt, B Mazin

Abstract:

As high pixel count Microwave Kinetic Inductance Detector (MKID) arrays become widely adopted, there is a growing demand for automated device readout calibration. These calibrations include ascertaining the optimal driving power for best pixel sensitivity, which, because of large variations in MKID behavior, is typically performed by manual inspection. This process takes roughly 1 hour per 1000 MKIDs, making the manual characterization of ten-kilopixel scale arrays unfeasible. We propose the concept of using a machine-learning algorithm, based on a convolution neural network (CNN) architecture, which should reliably tune ten-kilopixel scale MKID arrays on the order of several minutes.