Multiple density discontinuities in the merging galaxy cluster CIZA J2242.8+5301

CIZA J2242.8+5301, a merging galaxy cluster at z=0.19, hosts a double-relic system and a faint radio halo. Radio observations at frequencies ranging from a few MHz to several GHz have shown that the radio spectral index at the outer edge of the N relic corresponds to a shock of Mach number 4.6+/-1.1, under the assumptions of diffusive shock acceleration of thermal particles in the test particle regime. Here, we present results from new Chandra observations of the cluster. The Chandra surface brightness profile across the N relic only hints to a surface brightness discontinuity (<2-sigma detection). Nevertheless, our reanalysis of archival Suzaku data indicates a temperature discontinuity across the relic that is consistent with a Mach number of 2.5+/-0.5, in agreement with previously published results. This confirms that the Mach number at the shock traced by the N relic is much weaker than predicted from the radio. Puzzlingly, in the Chandra data we also identify additional inner small density discontinuities both on and off the merger axis. Temperature measurements on both sides of the discontinuities do not allow us to undoubtedly determine their nature, although a shock front interpretation seems more likely. We speculate that if the inner density discontinuities are indeed shock fronts, then they are the consequence of violent relaxation of the dark matter cores of the clusters involved in the merger.Comment: 11 pages, 11 figures. Accepted for publication in MNRA

The Entrainment-Limited Evolution of FR II Sources: Maximum Sizes and A Possible Connection to FR Is

We construct a simple theoretical model to investigate how entrainment gradually erodes high-speed FR II jets. This process is described by embedding a mixing-layer model developed originally to describe FR I objects in a self-similar model for the lobe structure of classical FR II sources. Following the classical FR II models, we assume that the lobe is dominated by the particles injected from the central jet. The entrainment produces a boundary shear layer which acts at the interface between the dense central jet and the less denser surrounding lobe, and the associated erosion of the jet places interesting limits on the maximum size of FR II sources. The model shows that this limit depends mainly on the initial bulk velocity of the relativistic jet triggered. The bulk velocities of FR IIs suggested by our model are in good agreement with that obtained from direct pc-scale observations on ordinary radio galaxies and quasars. Finally, we discuss how FR IIs may evolve into FR Is upon reaching their maximum, entrainment-limited sizes.Comment: 9 pages, 5 figures, accepted for publication in MNRA

Calibration of the galaxy cluster M_500-Y_X relation with XMM-Newton

The quantity Y_ X, the product of the X-ray temperature T_ X and gas mass M_ g, has recently been proposed as a robust low-scatter mass indicator for galaxy clusters. Using precise measurements from XMM-Newton data of a sample of 10 relaxed nearby clusters, spanning a Y_ X range of 10^13 -10^15 M_sun keV, we investigate the M_500-Y_ X relation. The M_500 - Y_ X data exhibit a power law relation with slope alpha=0.548 \pm 0.027, close to the self-similar value (3/5) and independent of the mass range considered. However, the normalisation is \sim 20% below the prediction from numerical simulations including cooling and galaxy feedback. We discuss two effects that could contribute to the normalisation offset: an underestimate of the true mass due to the HE assumption used in X-ray mass estimates, and an underestimate of the hot gas mass fraction in the simulations. A comparison of the functional form and scatter of the relations between various observables and the mass suggest that Y_ X may indeed be a better mass proxy than T_ X or M_g,500.Comment: 4 pages, 2 figures, accepted for publication in A&

Morphological classification of radio galaxies: Capsule Networks versus Convolutional Neural Networks

Next-generation radio surveys will yield an unprecedented amount of data, warranting analysis by use of machine learning techniques. Convolutional neural networks are the deep learning technique that has proven to be the most successful in classifying image data. Capsule networks are a more recently developed technique that use capsules comprised of groups of neurons, that describe properties of an image including the relative spatial locations of features. The current work explores the performance of different capsule network architectures against simpler convolutional neural network architectures, in reproducing the classifications into the classes of unresolved, FRI and FRII morphologies. We utilise images from a LOFAR survey which is the deepest, wide-area radio survey to date, revealing more complex radio-source structures compared to previous surveys, presenting further challenges for machine learning algorithms. The 4- and 8-layer convolutional networks attain an average precision of 93.3% and 94.3% respectively, compared to 89.7% obtained with the capsule network, when training on original and augmented images. Implementing transfer learning achieves a precision of 94.4%, that is within the confidence interval of the 8-layer convolutional network. The convolutional networks always outperform any variation of the capsule network, as they prove to be more robust to the presence of noise in images. The use of pooling appears to allow more freedom for the intra-class variability of radio galaxy morphologies, as well as reducing the impact of noise

Remnant radio-loud AGN in the Herschel-ATLAS field

Only a small fraction of observed active galactic nuclei (AGN) display large-scale radio emission associated with jets, yet these radio-loud AGN have become increasingly important in models of galaxy evolution. In determining the dynamics and energetics of the radio sources over cosmic time, a key question concerns what happens when their jets switch off. The resulting ‘remnant' radio-loud AGN have been surprisingly evasive in past radio surveys, and therefore statistical information on the population of radio-loud AGN in their dying phase is limited. In this paper, with the recent developments of Low-Frequency Array (LOFAR) and the Very Large Array, we are able to provide a systematically selected sample of remnant radio-loud AGN in the Herschel-ATLAS field. Using a simple core-detection method, we constrain the upper limit on the fraction of remnants in our radio-loud AGN sample to 9 per cent, implying that the extended lobe emission fades rapidly once the core/jets turn off. We also find that our remnant sample has a wide range of spectral indices (−1.5 ⩽ α1400150 ⩽ −0.5), confirming that the lobes of some remnants may possess flat spectra at low frequencies just as active sources do. We suggest that, even with the unprecedented sensitivity of LOFAR, our sample may still only contain the youngest of the remnant population