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

This document is the Accepted Manuscript version of the following article: Sarah V. White, Matt J. Jarvis, Eleni Kalfoutnzou, Martin J. Hardcastle, Aprajita Verma, Mose M. Cao Orjales, and Jason Stevens, 'Evidence that the AGN dominates the radio emission in z ~ 1 radio quiet quasars', Monthly Notices of the Royal Astronomical Society, first published online 3 February 2017, DOI: https://doi.org/10.1093/mnras/stx284 Key results are presented in Table 4 and Figure 7, which illustrates where the RQQs lie in relation to the far-infrared--radio correlation © 2017 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society.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 minimising 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 2 $\sigma$. This radio dataset 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 2-$\sigma$ 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.Peer reviewedFinal Accepted Versio

Radio Galaxy Zoo: Towards building the first multi-purpose foundation model for radio astronomy with self-supervised learning

In this work, we apply self-supervised learning with instance differentiation to learn a robust, multi-purpose representation for image analysis of resolved extragalactic continuum images. We train a multi-use model which compresses our unlabelled data into a structured, low dimensional representation which can be used for a variety of downstream tasks (e.g. classification, similarity search). We exceed baseline supervised Fanaroff-Riley classification performance by a statistically significant margin, with our model reducing the test set error by up to half. Our model is also able to maintain high classification accuracy with very few labels, with only 7.79% error when only using 145 labels. We further demonstrate that by using our foundation model, users can efficiently trade off compute, human labelling cost and test set accuracy according to their respective budgets, allowing for efficient classification in a wide variety of scenarios. We highlight the generalizability of our model by showing that it enables accurate classification in a label scarce regime with data from the new MIGHTEE survey without any hyper-parameter tuning, where it improves upon the baseline by ~8%. Visualizations of our labelled and un-labelled data show that our model's representation space is structured with respect to physical properties of the sources, such as angular source extent. We show that the learned representation is scientifically useful even if no labels are available by performing a similarity search, finding hybrid sources in the RGZ DR1 data-set without any labels. We show that good augmentation design and hyper-parameter choice can help achieve peak performance, while emphasising that optimal hyper-parameters are not required to obtain benefits from self-supervised pre-training

MeerKAT follow-up of enigmatic GLEAM 4-Jy (G4Jy) sources

We present the results from studying 140 radio sources in the GLEAM (GaLactic and Extragalactic All-sky MWA [Murchison Widefield Array]) 4-Jy (G4Jy) Sample. These sources were followed-up with MeerKAT to assess their radio morphology and enable host-galaxy identification, as existing radio images of 25 to 45-arcsec resolution do not provide sufficient information. We refer to these sources as the MeerKAT-2019 subset. The aim is to identify the host galaxy of these sources by visually inspecting the overlays comprising radio data from four surveys (at 150, 200, 843/1400, and 1300 MHz). Our morphological classification and host-galaxy identification relies upon the ~7-arcsec resolution images from MeerKAT (1300 MHz). Through the visual inspection of the overlays, 14 radio sources in the MeerKAT-2019 subset have wide-angle tail (WAT) morphology, 10 are head-tail, and 5 have X-, S-/Z-shaped morphology. Most of the remaining sources have the radio morphology of typical symmetric lobes. Of 140 sources, we find host galaxies for 98 sources, leaving 42 with no identified host galaxy. These 42 sources still have ambiguous identification even with higher resolution images from MeerKAT.Comment: 20 pages, 16 figures, 4 tables. Accepted in MNRA

Accretion and star formation in 'radio-quiet' quasars

Radio observations allow us to identify a wide range of active galactic nuclei (AGN), which play a significant role in the evolution of galaxies. Amongst AGN at low radio-luminosities is the 'radio-quiet' quasar (RQQ) population, but how they contribute to the total radio emission is under debate, with previous studies arguing that it is predominantly through star formation. In this talk, SVW summarised the results of recent papers on RQQs, including the use of far-infrared data to disentangle the radio emission from the AGN and that from star formation. This provides evidence that black-hole accretion, instead, dominates the radio emission in RQQs. In addition, we find that this accretion-related emission is correlated with the optical luminosity of the quasar, whilst a weaker luminosity-dependence is evident for the radio emission connected with star formation. What remains unclear is the process by which this accretion-related emission is produced. Understanding this for RQQs will then allow us to investigate how this type of AGN influences its surroundings. Such studies have important implications for modelling AGN feedback, and for determining the accretion and star-formation histories of the Universe.Comment: 5 pages, 2 figures, proceedings of IAU Symposium 356 on "Nuclear Activity in Galaxies Across Cosmic Time", October 201

Retelling racialized violence, remaking white innocence: the politics of interlocking oppressions in transgender day of remembrance

Transgender Day of Remembrance has become a significant political event among those resisting violence against gender-variant persons. Commemorated in more than 250 locations worldwide, this day honors individuals who were killed due to anti-transgender hatred or prejudice. However, by focusing on transphobia as the definitive cause of violence, this ritual potentially obscures the ways in which hierarchies of race, class, and sexuality constitute such acts. Taking the Transgender Day of Remembrance/Remembering Our Dead project as a case study for considering the politics of memorialization, as well as tracing the narrative history of the Fred F. C. Martinez murder case in Colorado, the author argues that deracialized accounts of violence produce seemingly innocent White witnesses who can consume these spectacles of domination without confronting their own complicity in such acts. The author suggests that remembrance practices require critical rethinking if we are to confront violence in more effective ways. Description from publisher's site: http://caliber.ucpress.net/doi/abs/10.1525/srsp.2008.5.1.2

A Retinoblastoma Orthologue Is Required for the Sensing of a Chalone in Dictyostelium discoideum

Retinoblastoma-like proteins regulate cell differentiation and inhibit cell proliferation. The Dictyostelium discoideum retinoblastoma orthologue RblA affects the differentiation of cells during multicellular development, but it is unclear whether RblA has a significant effect on Dictyostelium cell proliferation, which is inhibited by the secreted proteins AprA and CfaD. We found that rblA(−) cells in shaking culture proliferate to a higher density, die faster after reaching stationary density, and, after starvation, have a lower spore viability than wild-type cells, possibly because in shaking culture, rblA(−) cells have both increased cytokinesis and lower extracellular accumulation of CfaD. However, rblA(−) cells have abnormally slow proliferation on bacterial lawns. Recombinant AprA inhibits the proliferation of wild-type cells but not that of rblA(−) cells, whereas CfaD inhibits the proliferation of both wild-type cells and rblA(−) cells. Similar to aprA(−) cells, rblA(−) cells have a normal mass and protein accumulation rate on a per-nucleus basis, indicating that RblA affects cell proliferation but not cell growth. AprA also functions as a chemorepellent, and RblA is required for proper AprA chemorepellent activity despite the fact that RblA does not affect cell speed. Together, our data indicate that an autocrine proliferation-inhibiting factor acts through RblA to regulate cell density in Dictyostelium, suggesting that such factors may signal through retinoblastoma-like proteins to control the sizes of structures such as developing organs or tumors

The optically selected 1.4-GHz quasar luminosity function below 1 mJy

We present the radio luminosity function (RLF) of optically selected quasars below 1 mJy, constructed by applying a Bayesian-fitting stacking technique to objects well below the nominal radio flux density limit. We test the technique using simulated data, confirming that we can reconstruct the RLF over three orders of magnitude below the typical 5σ detection threshold. We apply our method to 1.4-GHz flux densities from the Faint Images of the Radio Sky at Twenty-Centimeters (FIRST) survey, extracted at the positions of optical quasars from the Sloan Digital Sky Survey over seven redshift bins up to z = 2.15, and measure the RLF down to two orders of magnitude below the FIRST detection threshold. In the lowest redshift bin (0.2 < z < 0.45), we find that our measured RLF agrees well with deeper data from the literature. The RLF for the radio-loud quasars flattens below log10[L1.4/WHz−1]≈25.5 and becomes steeper again below log10[L1.4/WHz−1]≈24.8⁠, where radio-quiet quasars start to emerge. The radio luminosity where radio-quiet quasars emerge coincides with the luminosity where star-forming galaxies are expected to start dominating the radio source counts. This implies that there could be a significant contribution from star formation in the host galaxies, but additional data are required to investigate this further. The higher redshift bins show a similar behaviour to the lowest z bin, implying that the same physical process may be responsible

The Cluster Mass Function from Early SDSS Data: Cosmological Implications

The mass function of clusters of galaxies is determined from 400 deg^2 of early commissioning imaging data of the Sloan Digital Sky Survey; ~300 clusters in the redshift range z = 0.1 - 0.2 are used. Clusters are selected using two independent selection methods: a Matched Filter and a red-sequence color magnitude technique. The two methods yield consistent results. The cluster mass function is compared with large-scale cosmological simulations. We find a best-fit cluster normalization relation of sigma_8*omega_m^0.6 = 0.33 +- 0.03 (for 0.1 ~< omega_m ~< 0.4), or equivalently sigma_8 = (0.16/omega_m)^0.6. The amplitude of this relation is significantly lower than the previous canonical value, implying that either omega_m is lower than previously expected (omega_m = 0.16 if sigma_8 = 1) or sigma_8 is lower than expected (sigma_8 = 0.7 if omega_m = 0.3). The best-fit mass function parameters are omega_m = 0.19 (+0.08,-0.07) and sigma_8 = 0.9 (+0.3,-0.2). High values of omega_m (>= 0.4) and low sigma_8 (=~ 2 sigma.Comment: AASTeX, 25 pages, including 7 figures, accepted for publication in ApJ, vol.585, March 200