arXiv subjects

Ray P. Norris

Publications and source records attributed to Ray P. Norris.

At least 55 records · Page 3Linked to original sources

arXiv2019

Radio Observations of Supernova Remnant G1.9+0.3

We present 1 to 10GHz radio continuum flux density, spectral index, polarisation and Rotation Measure (RM) images of the youngest known Galactic Supernova Remnant (SNR) G1.9+0.3, using observations from the Australia Telescope Compact Array (ATCA). We have conducted an expansion study spanning 8 epochs between 1984 and 2017, yielding results consistent with previous expansion studies of G1.9+0.3. We find a mean radio continuum expansion rate of ($0.78 \pm 0.09$) per cent year$^{-1}$ (or $\sim8900$ km s$^{-1}$ at an assumed distance of 8.5 kpc), although the expansion rate varies across the SNR perimeter. In the case of the most recent epoch between 2016 and 2017, we observe faster-than-expected expansion of the northern region. We find a global spectral index for G1.9+0.3 of $-0.81\pm0.02$ (76 MHz$-$10 GHz). Towards the northern region, however, the radio spectrum is observed to steepen significantly ($\sim -$1). Towards the two so called (east & west) "ears" of G1.9+0.3, we find very different RM values of 400-600 rad m$^{2}$ and 100-200 rad m$^{2}$ respectively. The fractional polarisation of the radio continuum emission reaches (19 $\pm$ 2)~per~cent, consistent with other, slightly older, SNRs such as Cas~A.

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arXiv2019

Identifying complex sources in large astronomical data using a coarse-grained complexity measure

The volume of data that will be produced by the next generation of astrophysical instruments represents a significant opportunity for making unplanned and unexpected discoveries. Conversely, finding unexpected objects or phenomena within such large volumes of data presents a challenge that may best be solved using computational and statistical approaches. We present the application of a coarse-grained complexity measure for identifying interesting observations in large astronomical data sets. This measure, which has been termed apparent complexity, has been shown to model human intuition and perceptions of complexity. Apparent complexity is computationally efficient to derive and can be used to segment and identify interesting observations in very large data sets based on their morphological complexity. We show, using data from the Australia Telescope Large Area Survey, that apparent complexity can be combined with clustering methods to provide an automated process for distinguishing between images of galaxies which have been classified as having simple and complex morphologies. The approach generalizes well when applied to new data after being calibrated on a smaller data set, where it performs better than tested classification methods using pixel data. This generalizability positions apparent complexity as a suitable machine-learning feature for identifying complex observations with unanticipated features.

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arXiv2019

Radio Galaxy Zoo: Unsupervised Clustering of Convolutionally Auto-encoded Radio-astronomical Images

This paper demonstrates a novel and efficient unsupervised clustering method with the combination of a Self-Organising Map (SOM) and a convolutional autoencoder. The rapidly increasing volume of radio-astronomical data has increased demand for machine learning methods as solutions to classification and outlier detection. Major astronomical discoveries are unplanned and found in the unexpected, making unsupervised machine learning highly desirable by operating without assumptions and labelled training data. Our approach shows SOM training time is drastically reduced and high-level features can be clustered by training on auto-encoded feature vectors instead of raw images. Our results demonstrate this method is capable of accurately separating outliers on a SOM with neighbourhood similarity and K-means clustering of radio-astronomical features complexity. We present this method as a powerful new approach to data exploration by providing a detailed understanding of the morphology and relationships of Radio Galaxy Zoo (RGZ) dataset image features which can be applied to new radio survey data.

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arXiv2019

Radio Galaxy Zoo: The Distortion of Radio Galaxies by Galaxy Clusters

We study the impact of cluster environment on the morphology of a sample of 4304 extended radio galaxies from Radio Galaxy Zoo. A total of 87% of the sample lies within a projected 15 Mpc of an optically identified cluster. Brightest cluster galaxies (BCGs) are more likely than other cluster members to be radio sources, and are also moderately bent. The surface density as a function of separation from cluster center of non-BCG radio galaxies follows a power law with index $-1.10\pm 0.03$ out to $10~r_{500}$ ($\sim 7~$Mpc), which is steeper than the corresponding distribution for optically selected galaxies. Non-BCG radio galaxies are statistically more bent the closer they are to the cluster center. Within the inner $1.5~r_{500}$ ($\sim 1~$Mpc) of a cluster, non-BCG radio galaxies are statistically more bent in high-mass clusters than in low-mass clusters. Together, we find that non-BCG sources are statistically more bent in environments that exert greater ram pressure. We use the orientation of bent radio galaxies as an indicator of galaxy orbits and find that they are preferentially in radial orbits. Away from clusters, there is a large population of bent radio galaxies, limiting their use as cluster locators; however, they are still located within statistically overdense regions. We investigate the asymmetry in the tail length of sources that have their tails aligned along the radius vector from the cluster center, and find that the length of the inward-pointing tail is weakly suppressed for sources close to the center of the cluster.

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arXiv2019

The first Super Massive Black Holes: indications from models for future observations

We present an exploration of the expected detection of the earliest Active Galactic Nuclei (AGN) in the Universe from state-of-art galaxy formation and evolution semi-analytic models and hydro-dynamical simulations. We estimate the number and radiative characteristics of Super Massive Black Holes (SMBHs) at $z\geq 6$, a redshift range that will be intensively explored by the next generation of telescopes, in particular in the radio through the Square Kilometre Array (SKA) and at high energies with ESA's Athena X-ray Observatory. We find that Athena will be able to observe over 5000 AGN/$\rm deg^2$ at the Epoch of Re-ionization (EoR), $6\leq z \leq 10$. Similarly, for the same redshift range the models/simulations suggest that SKA will detect at least 400 AGN/$\rm deg^2$. Additionally, we stress the importance of the volume of the simulation box as well as the initial physical conditions of the models/simulations on their effect on the luminosity functions (LFs) and the creation of the most massive SMBHs that we currently observe at the EoR. Furthermore, following the evolution of the accretion mode of the SMBHs in each model/simulation, we show that, while the quasar dominates over the radio mode at the EoR, detection at radio wavelengths still reaches significant numbers even at the highest redshifts. Finally, we present the effect that the radiative efficiency has on the LFs by comparing results produced with a constant value for the radiative efficiency and more complex calculations based on the spin of each SMBH.

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arXiv2019

Probing $Λ$CDM cosmology with the Evolutionary Map of the Universe survey

The Evolutionary Map of the Universe (EMU) is an all-sky survey in radio-continuum which uses the Australian SKA Pathfinder (ASKAP). Using galaxy angular power spectrum and the integrated Sachs-Wolfe effect, we study the potential of EMU to constrain models beyond $Λ$CDM (i.e., local primordial non-Gaussianity, dynamical dark energy, spatial curvature and deviations from general relativity), for different design sensitivities. We also include a multi-tracer analysis, distinguishing between star-forming galaxies and galaxies with an active galactic nucleus, to further improve EMU's potential. We find that EMU could measure the dark energy equation of state parameters around 35\% more precisely than existing constraints, and that the constraints on $f_{\rm NL}$ and modified gravity parameters will improve up to a factor $\sim2$ with respect to Planck and redshift space distortions measurements. With this work we demonstrate the promising potential of EMU to contribute to our understanding of the Universe.

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arXiv2019

A Comparison of Photometric Redshift Techniques for Large Radio Surveys

Future radio surveys will generate catalogues of tens of millions of radio sources, for which redshift estimates will be essential to achieve many of the science goals. However, spectroscopic data will be available for only a small fraction of these sources, and in most cases even the optical and infrared photometry will be of limited quality. Furthermore, radio sources tend to be at higher redshift than most optical sources and so a significant fraction of radio sources hosts differ from those for which most photometric redshift templates are designed. We therefore need to develop new techniques for estimating the redshifts of radio sources. As a starting point in this process, we evaluate a number of machine-learning techniques for estimating redshift, together with a conventional template-fitting technique. We pay special attention to how the performance is affected by the incompleteness of the training sample and by sparseness of the parameter space or by limited availability of ancillary multi-wavelength data. As expected, we find that the quality of the photometric-redshift degrades as the quality of the photometry decreases, but that even with the limited quality of photometry available for all sky-surveys, useful redshift information is available for the majority of sources, particularly at low redshift. We find that a template-fitting technique performs best with high-quality and almost complete multi-band photometry, especially if radio sources that are also X-ray emitting are treated separately. When we reduced the quality of photometry to match that available for the EMU all-sky radio survey, the quality of the template-fitting degraded and became comparable to some of the machine learning methods. Machine learning techniques currently perform better at low redshift than at high redshift, because of incompleteness of the currently available training data at high redshifts.

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arXiv2018

The Redshift Distribution of Infrared-Faint Radio Sources

Infrared-Faint Radio Sources (IFRSs) are an important class of high-redshift active galaxy, and potentially important as a means of discovering more high-redshift radio sources, but only 25 IFRSs had redshifts prior to this paper. Here we increase the number of IFRSs with known spectroscopic redshifts by a factor of about 5 to 131, with redshifts up to z=4.387, and a median redshift of z = 2.68. The IFRS redshift distribution overlaps with the high-z radio galaxy (HzRG) redshift distribution but is significantly narrower, suggesting that the IFRSs are a subset of the larger class of HzRGs. We also confirm and measure the proposed correlation between redshift and 3.6 $μ$m flux density, making it possible to use this correlation to find even higher redshift radio sources. Many more high-redshift sources are probably present in existing radio survey catalogues.

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arXiv2018

Radio Galaxy Zoo: ClaRAN - A Deep Learning Classifier for Radio Morphologies

The upcoming next-generation large area radio continuum surveys can expect tens of millions of radio sources, rendering the traditional method for radio morphology classification through visual inspection unfeasible. We present ClaRAN - Classifying Radio sources Automatically with Neural networks - a proof-of-concept radio source morphology classifier based upon the Faster Region-based Convolutional Neutral Networks (Faster R-CNN) method. Specifically, we train and test ClaRAN on the FIRST and WISE images from the Radio Galaxy Zoo Data Release 1 catalogue. ClaRAN provides end users with automated identification of radio source morphology classifications from a simple input of a radio image and a counterpart infrared image of the same region. ClaRAN is the first open-source, end-to-end radio source morphology classifier that is capable of locating and associating discrete and extended components of radio sources in a fast (< 200 milliseconds per image) and accurate (>= 90 %) fashion. Future work will improve ClaRAN's relatively lower success rates in dealing with multi-source fields and will enable ClaRAN to identify sources on much larger fields without loss in classification accuracy.

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arXiv2018

Preliminary results of using k-Nearest Neighbours Regression to estimate the redshift of radio selected datasets

In the near future, all-sky radio surveys are set to produce catalogues of tens of millions of sources with limited multi-wavelength photometry. Spectroscopic redshifts will only be possible for a small fraction of these new-found sources. In this paper, we provide the first in-depth investigation into the use of k-Nearest Neighbours Regression for the estimation of redshift of these sources. We use the Australia Telescope Large Area Survey radio data, combined with the Spitzer Wide-Area Infrared Extragalactic Survey infra-red, the Dark Energy Survey optical and the Australian Dark Energy Survey spectroscopic survey data. We then reduce the depth of photometry to match what is expected from upcoming Evolutionary Map of the Universe survey, testing against both data sets. To examine the generalisation of our methods, we test one of the sub-fields of Australia Telescope Large Area Survey against the other. We achieve an outlier rate of ~10% across all tests, showing that the k-Nearest Neighbours regression algorithm is an acceptable method of estimating redshift, and would perform better given a sample training set with uniform redshift coverage.

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arXiv2018

The Spatial Correlation of Bent-Tail Galaxies and Galaxy Clusters

We have completed a deep radio continuum survey covering 86 square degrees of the Spitzer-South Pole Telescope deep field to test whether bent-tail galaxies are associated with galaxy clusters. We present a new catalogue of 22 bent-tail galaxies and a further 24 candidate bent-tail galaxies. Surprisingly, of the 8 bent-tail galaxies with photometric redshifts, only two are associated with known clusters. While the absence of bent-tail sources in known clusters may be explained by effects such as sensitivity, the absence of known clusters associated with most bent-tail galaxies casts doubt upon current models of bent-tail galaxies.

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arXiv2018

The First VLBI Detection of a Spiral DRAGN Core

The existence of spiral DRAGNs challenges standard galaxy formation theories. We present the first observation of 0313$-$192, the archetypal spiral DRAGN, at VLBI resolutions. Spiral DRAGNs are Double Radio Sources Associated with Galactic Nuclei (DRAGNs) that are hosted by spiral galaxies. 0313$-$192 is an edge-on spiral galaxy that appears to host a 360 kpc double-lobed radio source. The core of this galaxy is clearly detected at L, S, and X-bands using the VLBA, signifying an ongoing active nucleus in the galaxy. This rules out the possibility that the spiral DRAGN is merely a chance alignment. The radio core has L$_{1.4\,GHz} \sim 3.0 \times 10^{23}$W Hz$^{-1}$. Radio components are detected to the South-West of the core, but there are no detections of a counterjet. Assuming a symmetric, relativistic jet, we estimate an upper limit to the inclination angle of $θ\lesssim 72$ degrees. The VLBI-detected radio jet components are extremely well-aligned with the larger-scale radio source suggesting little to no jet disruption or interaction with the ISM of the host galaxy.

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arXiv2018

High-resolution Observations of Low-luminosity Gigahertz-Peaked Spectrum and Compact Steep Spectrum Sources

We present Very Long Baseline Interferometry observations of a faint and low-luminosity ($L_{\rm 1.4 GHz} < 10^{27}~\mbox{W Hz}^{-1}$) Gigahertz-Peaked Spectrum (GPS) and Compact Steep Spectrum (CSS) sample. We select eight sources from deep radio observations that have radio spectra characteristic of a GPS or CSS source and an angular size of $θ\lesssim 2$ arcsec, and detect six of them with the Australian Long Baseline Array. We determine their linear sizes, and model their radio spectra using Synchrotron Self Absorption (SSA) and Free Free Absorption (FFA) models. We derive statistical model ages, based on a fitted scaling relation, and spectral ages, based on the radio spectrum, which are generally consistent with the hypothesis that GPS and CSS sources are young and evolving. We resolve the morphology of one CSS source with a radio luminosity of $10^{25}~\mbox{W Hz}^{-1}$, and find what appear to be two hotspots spanning 1.7 kpc. We find that our sources follow the turnover-linear size relation, and that both homogenous SSA and an inhomogeneous FFA model can account for the spectra with observable turnovers. All but one of the FFA models do not require a spectral break to account for the radio spectrum, while all but one of the alternative SSA and power law models do require a spectral break to account for the radio spectrum. We conclude that our low-luminosity sample is similar to brighter samples in terms of their spectral shape, turnover frequencies, linear sizes, and ages, but cannot test for a difference in morphology.

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arXiv2017

Low Frequency Radio Constraints on the Synchrotron Cosmic Web

We present a search for the synchrotron emission from the synchrotron cosmic web by cross correlating 180MHz radio images from the Murchison Widefield Array with tracers of large scale structure (LSS). We use two versions of the radio image covering $21.76\times 21.76$ degrees with point sources brighter than 0.05 Jy subtracted, with and without filtering of Galactic emission. As tracers of the LSS we use the Two-Micron-All-Sky-Survey (2MASS) and the Widefield InfraRed Explorer (WISE) redshift catalogues to produce galaxy number density maps. The cross correlation functions all show peak amplitudes at zero degrees, decreasing with varying slopes towards zero correlation over a range of one degree. The cross correlation signals include components from point source, Galactic, and extragalactic diffuse emission. We use models of the diffuse emission from smoothing the density maps with Gaussians of sizes 1-4 Mpc to find limits on the cosmic web components. From these models we find surface brightness 99.7 per cent upper limits in the range of 0.09-2.20 mJy beam$^{-1}$ (average beam size of 2.6 arcmin), corresponding to 0.01-0.30 mJy arcmin$^{-2}$. Assuming equipartition between energy densities of cosmic rays and the magnetic field, the flux density limits translate to magnetic field strength limits of 0.03-1.98 $μ$G, depending heavily on the spectral index. We conclude that for a 3$σ$ detection of 0.1 $μ$G magnetic field strengths via cross correlations, image depths of sub-mJy to sub-$μ$Jy are necessary. We include discussion on the treatment and effect of extragalactic point sources and Galactic emission, and next steps for building on this work.

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arXiv2016

Astroinformatics Challenges from Next-generation Radio Continuum Surveys

The tens of millions of radio sources to be detected with next-generation surveys pose new challenges, quite apart from the obvious ones of processing speed and data volumes. For example, existing algorithms are inadequate for source extraction or cross-matching radio and optical/IR sources, and a new generation of algorithms are needed using machine learning and other techniques. The large numbers of sources enable new ways of testing astrophysical models, using a variety of "large-n astronomy" techniques such as statistical redshifts. Furthermore, while unexpected discoveries account for some of the most significant discoveries in astronomy, it will be difficult to discover the unexpected in large volumes of data, unless specific software is developed to mine the data for the unexpected.

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arXiv2016

WTF? Discovering the Unexpected in next-generation radio continuum surveys

Most major discoveries in astronomy have come from unplanned discoveries made by surveying the Universe in a new way, rather than by testing a hypothesis or conducting an investigation with planned outcomes. Next generation radio continuum surveys such as the Evolutionary Map of the Universe (EMU: the radio continuum survey on the new Australian SKA Pathfinder telescope), will significantly expand the volume of observational phase space, so we can be reasonably confident that we will stumble across unexpected new phenomena or new types of object. However, the complexity of the instrument and the large data volumes mean that it may be non-trivial to identify them. On the other hand, if we don't, then we may be missing out on the most exciting science results from EMU. We have therefore started a project called "WTF", which explicitly aims to mine EMU data to discover unexpected science that is not part of our primary science goals, using a variety of machine-learning techniques and algorithms. Although targeted specifically at EMU, we expect this approach will have broad applicability to astronomical survey data.

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arXiv2016

Infrared-Faint Radio Sources in the SERVS deep fields: Pinpointing AGNs at high redshift

Infrared-Faint Radio Sources (IFRS) represent an unexpected class of objects relatively bright at radio wavelength, but unusually faint at infrared (IR) and optical wavelengths. A recent and extensive campaign on the radio-brightest IFRSs (S_{1.4GHz} >= 10 mJy) has provided evidence that most of them (if not all) contain an AGN. Still uncertain is the nature of the radio-faintest ones (S_{1.4GHz} <= 1 mJy). The scope of this paper is to assess the nature of the radio-faintest IFRSs, testing their classification and improving the knowledge of their IR properties making use of the most sensitive IR survey available so far: the Spitzer Extragalactic Representative Volume Survey (SERVS). We also explore how the criteria of IFRSs can be fine-tuned to pinpoint radio-loud AGNs at very high redshift (z > 4). We analysed a number of IFRS samples identified in SERVS fields, including a new sample (21 sources) extracted from the Lockman Hole. 3.6 and 4.5 mum IR counterparts of the 64 sources located in the SERVS fields were searched for, and, when detected, their IR properties were studied. We compared the radio/IR properties of the IR-detected IFRSs with those expected for a number of known classes of objects. We found that they are mostly consistent with a mixture of high-redshift (z >= 3) radio-loud AGNs. The faintest ones (S_{1.4GHz} ~ 100 muJy), however, could be also associated with nearer (z ~ 2) dust-enshrouded star-burst galaxies. We also argue that, while IFRSs with radio-to-IR ratios > 500 can very efficiently pinpoint radio-loud AGNs at redshift 2 < z < 4, lower radio-to-IR ratios (~ 100--200) are expected for higher redshift radio-loud AGNs.

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arXiv2016

Dawes Review 5: Australian Aboriginal Astronomy and Navigation

The traditional cultures of Aboriginal Australians include a significant astronomical component, perpetuated through oral tradition, ceremony, and art. This astronomical knowledge includes a deep understanding of the motion of objects in the sky, which was used for practical purposes such as constructing calendars and for navigation. There is also evidence that traditional Aboriginal Australians made careful records and measurements of cyclical phenomena, recorded unexpected phenomena such as eclipses and meteorite impacts, and could determine the cardinal points to an accuracy of a few degrees. Putative explanations of celestial phenomena appear throughout the oral record, suggesting traditional Aborig- inal Australians sought to understand the natural world around them, in the same way as modern scientists, but within their own cultural context. There is also a growing body of evidence for sophisticated navigational skills, including the use of astronomically based songlines. Songlines are effectively oral maps of the landscape, and are an efficient way of transmitting oral navigational skills in cultures that do not have a written language. The study of Aboriginal astronomy has had an impact extending beyond mere academic curiosity, facilitating cross-cultural understanding, demonstrating the intimate links between science and culture, and helping students to engage with science.

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