Browsing by Author "Heywood, Ian"
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Item MIGHTEE-Hi: The relation between the Hi gas in galaxies and the cosmic web(Oxford University Press, 2022) Tudorache, Madalina N.; Jarvis, Matthew J.; Heywood, IanWe study the 3D axis of rotation (3D spin) of 77 Hi galaxies from the MIGHTEE-Hi Early Science observations, and its relation to the filaments of the cosmic web. For this Hi-selected sample, the alignment between the spin axis and the closest filament (|cos 𝜓|) is higher for galaxies closer to the filaments, with h|cos 𝜓|i = 0.66 ± 0.04 for galaxies < 5 Mpc from their closest filament compared to h|cos 𝜓|i = 0.37±0.08 for galaxies at 5 < 𝑑 < 10 Mpc. We find that galaxies with a low Hi-to-stellar mass ratio (log10 (𝑀HI/𝑀★) < 0.11) are more aligned with their closest filaments, with h|cos 𝜓|i = 0.58 ± 0.04; whilst galaxies with (log10 (𝑀HI/𝑀★) > 0.11) tend to be mis-aligned, with h|cos 𝜓|i = 0.44 ± 0.04. We find tentative evidence that the spin axis of Hi-selected galaxies tend to be aligned with associated filaments (𝑑 < 10 Mpc), but this depends on the gas fractions. Galaxies that have accumulated more stellar mass compared to their gas mass tend towards stronger alignment.Item The preferentially magnified active nucleus in IRAS F10214+4724 - III. VLBI observations of the radio core(Oxford University Press, 2013) Deane, Roger P.; Rawlings, S.; Jarvis, Matt; Garrett, M. A.; Heywood, Ian; Klöckner, H. R.; Marshall, P. J.; McKean, J. P.We report 1.7GHz very long baseline interferometry (VLBI) observations of IRAS F10214+4724, a lensed z = 2.3 obscured quasar with prodigious star formation. We detect what we argue to be the obscured active nucleus with an effective angular resolution of <50pc at z = 2.3. The S1.7 =210µJy (9σ) detection of this unresolved source is located within the Hubble Space Telescope rest-frame ultraviolet/optical arc, however, 100 mas northwards of the arc centre of curvature. This leads to a source-plane inversion that places the European VLBI Network detection to within milliarcseconds of the modelled cusp caustic, resulting in a very large magnification (μ ∼70), over an order of magnitude larger than the CO (1→0) derived magnification of a spatially resolved Jansky Very Large Array (JVLA) map, using the same lens model. We estimate the quasar bolometric luminosity from a number of independent techniques and with our X-ray modelling find evidence that the AGN may be close to Compton thick, with an intrinsic bolometric luminosity of log10( Lbol, QSO /L ) = 11.34 ± 0.27dex. We make the first black hole mass estimate of IRAS F10214+4724 and find log10(MBH/M ) = 8.36 ± 0.56 which suggests a low black hole accretion rate (λ = ˙M/ ˙ MEdd ∼3±7 2 percent). We find evidence for an MBH/Mspheroid ratio that is one to two orders of magnitude larger than that of submillimetre galaxies (SMGs) at z ∼ 2. At face value, this suggests that IRAS F10214+4724 has undergone a different evolutionary path compared to SMGs at the same epoch. A primary result of this work is the demonstration that emission regions of different sizes and positions can undergo significantly different magnification boosts (>1dex) and therefore distort our view of high-redshift, gravitationally lensed galaxies.Item Sample variance, source clustering and their influence on the counts of faint radio sources(Oxford University Press, 2013) Heywood, Ian; Jarvis, Matt; Condon, James J.The shape of the curves defined by the counts of radio sources per unit area as a function of their flux density was one of the earliest cosmological probes. Radio source counts continue to be an area of astrophysical interest as they can be used to study the relative populations of galaxy types in the Universe (as well as investigate any cosmological evolution in their respective luminosity functions). They are also a vital consideration for determining howsource confusion may limit the depth of a radio interferometer observation, and are essential for characterizing the extragalactic foregrounds in cosmicmicrowave background experiments. There is currently no consensus as to the relative populations of the faintest (sub-mJy) source types, where the counts show a turn-up. Most of the source count data in this regime are gathered from multiple observations that each use a deep, single pointing with an interferometric radio telescope. These independent count measurements exhibit large amounts of scatter (factors of the order of a few) that significantly exceeds their respective stated uncertainties. In this paper, we use a simulation of the extragalactic radio continuum emission to assess the level at which sample variance may be the cause of the scatter. We find that the scatter induced by sample variance in the simulated counts decreases towards lower flux density bins as the raw source counts increase. The field-to-field variations make significant contributions to the scatter in the measurements of counts derived from deep observations that consist of a single pointing, and could even be the sole cause at >100 μJy. We present a method for evaluating the flux density limit that a radio survey must reach in order to reduce the count uncertainty induced by sample variance to a specific value. We also derive a method for correcting Poisson errors on source counts from existing and future deep radio surveys in order to include the uncertainties due to the cosmological clustering of sources. A conclusive empirical constraint on the effect of sample variance at these low luminosities is unlikely to arise until the completion of future large-scale radio surveys with next-generation radio telescopes.Item The discovery of a z = 0.7092 oh megamaser with the mightee survey(Oxford University Press, 2024) Jarvis, Matthew; Baker, Andrew; Heywood, IanWe present the discovery of the most distant OH megamaser (OHM) to be observed in the main lines, using data from the MeerKAT International Giga-Hertz Tiered Extragalactic Exploration (MIGHTEE) survey. At a newly measured redshift of z = 0.7092, the system has strong emission in both the 1665 MHz (L ≈ 2500 L-) and 1667 MHz (L ≈ 4.5 × 104 L-) transitions, with both narrow and broad components. We interpret the broad line as a high-velocity-dispersion component of the 1667 MHz transition, with velocity v ∼330 km s-1 with respect to the systemic velocity. The host galaxy has a stellar mass of M = 2.95 × 1010 M- and a star formation rate of SFR = 371 M- yr-1, placing it ∼1.5 dex above the main sequence for star-forming galaxies at this redshift, and can be classified as an ultraluminous infrared galaxy. Alongside the optical imaging data, which exhibit evidence for a tidal tail, this suggests that the OHM arises from a system that is currently undergoing a merger, which is stimulating star formation and providing the necessary conditions for pumping the OH molecule to saturationItem A unique, ring-like radio source with quadrilateral structure detected with machine learning(Oxford University Press, 2023) Lochner, Michelle; Rudnick, Lawrence; Heywood, IanWe report the discovery of a unique object in the MeerKAT Galaxy Cluster Le gacy Survey (MGCLS) using the machine learning anomaly detection framework ASTRONOMALY. This strange, ring-like source is 30 from the MGCLS field centred on Abell 209, and is not readily explained by simple physical models. With an assumed host galaxy at redshift 0.55, the luminosity (10 25 W Hz −1) is comparable to powerful radio galaxies. The source consists of a ring of emission 175 kpc across, quadrilateral enhanced brightness regions bearing resemblance to radio jets, two ‘ears’ separated by 368 kpc, and a diffuse envelope. All of the structures appear spectrally steep, ranging from −1.0 to −1.5. The ring has high polarization (25 per cent) except on the bright patches (< 10 per cent). We compare this source to the Odd Radio Circles recently discovered in ASKAP data and discuss several possible physical models, including a termination shock from starburst activity, an end-on radio galaxy, and a supermassive black hole merger event. No simple model can easily explain the observed structure of the source. This work, as well as other recent discoveries, demonstrates the power of unsupervised machine learning in mining large data sets for scientifically interesting sources.