arXiv subjects

R. P. Norris

Publications and source records attributed to R. P. Norris.

At least 55 records · Page 3Linked to original sources

arXiv2019

Discovery of a Pulsar-powered Bow Shock Nebula in the Small Magellanic Cloud Supernova Remnant DEMS5

We report the discovery of a new Small Magellanic Cloud Pulsar Wind Nebula (PWN) at the edge of the Supernova Remnant (SNR)-DEM S5. The pulsar powered object has a cometary morphology similar to the Galactic PWN analogs PSR B1951+32 and 'the mouse'. It is travelling supersonically through the interstellar medium. We estimate the Pulsar kick velocity to be in the range of 700-2000 km/s for an age between 28-10 kyr. The radio spectral index for this SNR PWN pulsar system is flat (-0.29 $\pm$ 0.01) consistent with other similar objects. We infer that the putative pulsar has a radio spectral index of -1.8, which is typical for Galactic pulsars. We searched for dispersion measures (DMs) up to 1000 cm/pc^3 but found no convincing candidates with a S/N greater than 8. We produce a polarisation map for this PWN at 5500 MHz and find a mean fractional polarisation of P $\sim 23$ percent. The X-ray power-law spectrum (Gamma $\sim 2$) is indicative of non-thermal synchrotron emission as is expected from PWN-pulsar system. Finally, we detect DEM S5 in Infrared (IR) bands. Our IR photometric measurements strongly indicate the presence of shocked gas which is expected for SNRs. However, it is unusual to detect such IR emission in a SNR with a supersonic bow-shock PWN. We also find a low-velocity HI cloud of $\sim 107$ km/s which is possibly interacting with DEM S5. SNR DEM S5 is the first confirmed detection of a pulsar-powered bow shock nebula found outside the Galaxy.

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arXiv2019

Radio Galaxy Zoo: Knowledge Transfer Using Rotationally Invariant Self-Organising Maps

With the advent of large scale surveys the manual analysis and classification of individual radio source morphologies is rendered impossible as existing approaches do not scale. The analysis of complex morphological features in the spatial domain is a particularly important task. Here we discuss the challenges of transferring crowdsourced labels obtained from the Radio Galaxy Zoo project and introduce a proper transfer mechanism via quantile random forest regression. By using parallelized rotation and flipping invariant Kohonen-maps, image cubes of Radio Galaxy Zoo selected galaxies formed from the FIRST radio continuum and WISE infrared all sky surveys are first projected down to a two-dimensional embedding in an unsupervised way. This embedding can be seen as a discretised space of shapes with the coordinates reflecting morphological features as expressed by the automatically derived prototypes. We find that these prototypes have reconstructed physically meaningful processes across two channel images at radio and infrared wavelengths in an unsupervised manner. In the second step, images are compared with those prototypes to create a heat-map, which is the morphological fingerprint of each object and the basis for transferring the user generated labels. These heat-maps have reduced the feature space by a factor of 248 and are able to be used as the basis for subsequent ML methods. Using an ensemble of decision trees we achieve upwards of 85.7% and 80.7% accuracy when predicting the number of components and peaks in an image, respectively, using these heat-maps. We also question the currently used discrete classification schema and introduce a continuous scale that better reflects the uncertainty in transition between two classes, caused by sensitivity and resolution limits.

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arXiv2018

Radio Galaxy Zoo: Observational evidence for environment as the cause of radio source asymmetry

We investigate the role of environment on radio galaxy properties by constructing a sample of large ($\gtrsim100$~kpc), nearby ($z<0.3$) radio sources identified as part of the Radio Galaxy Zoo citizen science project. Our sample consists of 16 Fanaroff-Riley Type II (FR-II) sources, 6 FR-I sources, and one source with a hybrid morphology. FR-I sources appear to be hosted by more massive galaxies, consistent with previous studies. In the FR-II sample, we compare the degree of asymmetry in radio lobe properties to asymmetry in the radio source environment, quantified through optical galaxy clustering. We find that the length of radio lobes in FR-II sources is anti-correlated with both galaxy clustering and lobe luminosity. These results are in quantitative agreement with predictions from radio source dynamical models, and suggest that galaxy clustering provides a useful proxy for the ambient gas density distribution encountered by the radio lobes.

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arXiv2018

Radio Galaxy Zoo: Machine learning for radio source host galaxy cross-identification

We consider the problem of determining the host galaxies of radio sources by cross-identification. This has traditionally been done manually, which will be intractable for wide-area radio surveys like the Evolutionary Map of the Universe (EMU). Automated cross-identification will be critical for these future surveys, and machine learning may provide the tools to develop such methods. We apply a standard approach from computer vision to cross-identification, introducing one possible way of automating this problem, and explore the pros and cons of this approach. We apply our method to the 1.4 GHz Australian Telescope Large Area Survey (ATLAS) observations of the Chandra Deep Field South (CDFS) and the ESO Large Area ISO Survey South 1 (ELAIS-S1) fields by cross-identifying them with the Spitzer Wide-area Infrared Extragalactic (SWIRE) survey. We train our method with two sets of data: expert cross-identifications of CDFS from the initial ATLAS data release and crowdsourced cross-identifications of CDFS from Radio Galaxy Zoo. We found that a simple strategy of cross-identifying a radio component with the nearest galaxy performs comparably to our more complex methods, though our estimated best-case performance is near 100 per cent. ATLAS contains 87 complex radio sources that have been cross-identified by experts, so there are not enough complex examples to learn how to cross-identify them accurately. Much larger datasets are therefore required for training methods like ours. We also show that training our method on Radio Galaxy Zoo cross-identifications gives comparable results to training on expert cross-identifications, demonstrating the value of crowdsourced training data.

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arXiv2018

VLBA+GBT observations of the COSMOS field and radio source counts at 1.4 GHz

We present very long baseline interferometry (VLBI) observations of 179 radio sources in the COSMOS field with extremely high sensitivity using the Green Bank Telescope (GBT) together with the Very Long Baseline Array (VLBA) (VLBA+GBT) at 1.4 GHz, to explore the faint radio population in the flux density regime of tens of $μ$Jy. Here, the identification of active galactic nuclei (AGN) is based on the VLBI detection of the source, i.e., it is independent of X-ray or infrared properties. The milli-arcsecond resolution provided by the VLBI technique implies that the detected sources must be compact and have large brightness temperatures, and therefore they are most likely AGN (when the host galaxy is located at z$\geq$0.1). On the other hand, this technique allows us to only positively identify when a radio-active AGN is present, i.e., we cannot affirm that there is no AGN when the source is not detected. For this reason, the number of identified AGN using VLBI should be always treated as a lower limit. We present a catalogue containing the 35 radio sources detected with the VLBA+GBT, 10 of which were not previously detected using only the VLBA. We have constructed the radio source counts at 1.4 GHz using the samples of the VLBA and VLBA+GBT detected sources of the COSMOS field to determine a lower limit for the AGN contribution to the faint radio source population. We found an AGN contribution of >40-75% at flux density levels between 150 $μ$Jy and 1 mJy. This flux density range is characterised by the upturn of the Euclidean-normalised radio source counts, which implies a contribution of a new population. This result supports the idea that the sub-mJy radio population is composed of a significant fraction of radio-emitting AGN, rather than solely by star-forming galaxies, in agreement with previous studies.

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arXiv2018

The XMM-SERVS survey: new XMM-Newton point-source catalog for the XMM-LSS field

We present an X-ray point-source catalog from the XMM-Large Scale Structure survey region (XMM-LSS), one of the XMM-Spitzer Extragalactic Representative Volume Survey (XMM-SERVS) fields. We target the XMM-LSS region with $1.3$ Ms of new XMM-Newton AO-15 observations, transforming the archival X-ray coverage in this region into a 5.3 deg$^2$ contiguous field with uniform X-ray coverage totaling $2.7$ Ms of flare-filtered exposure, with a $46$ ks median PN exposure time. We provide an X-ray catalog of 5242 sources detected in the soft (0.5-2 keV), hard (2-10 keV), and/or full (0.5-10 keV) bands with a 1% expected spurious fraction determined from simulations. A total of 2381 new X-ray sources are detected compared to previous source catalogs in the same area. Our survey has flux limits of $1.7\times10^{-15}$, $1.3\times10^{-14}$, and $6.5\times10^{-15}$ erg cm$^{-2}$ s$^{-1}$ over 90% of its area in the soft, hard, and full bands, respectively, which is comparable to those of the XMM-COSMOS survey. We identify multiwavelength counterpart candidates for 99.9% of the X-ray sources, of which 93% are considered as reliable based on their matching likelihood ratios. The reliabilities of these high-likelihood-ratio counterparts are further confirmed to be $\approx 97$% reliable based on deep Chandra coverage over $\approx 5$% of the XMM-LSS region. Results of multiwavelength identifications are also included in the source catalog, along with basic optical-to-infrared photometry and spectroscopic redshifts from publicly available surveys. We compute photometric redshifts for X-ray sources in 4.5 deg$^2$ of our field where forced-aperture multi-band photometry is available; $>70$% of the X-ray sources in this subfield have either spectroscopic or high-quality photometric redshifts.

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arXiv2018

Giant galaxy growing from recycled gas: ALMA maps the circumgalactic molecular medium of the Spiderweb in [CI]

The circumgalactic medium (CGM) of the massive Spiderweb Galaxy, a conglomerate of merging proto-cluster galaxies at z=2.2, forms an enriched interface where feedback and recycling act on accreted gas. This is shown by observations of [CI], CO(1-0) and CO(4-3) performed with the Atacama Large Millimeter Array (ALMA) and Australia Telescope Compact Array (ATCA). [CI] and CO(4-3) are detected across ~50 kpc, following the distribution of previously detected low-surface-brightness CO(1-0) across the CGM. This confirms our previous results on the presence of a cold molecular halo. The central radio galaxy MRC1138-262 shows a very high global $L'_{\rm CO(4-3)}$/$L'_{\rm CO(1-0)}$ ~ 1, suggesting that mechanisms other than FUV-heating by star formation prevail at the heart of the Spiderweb Galaxy. Contrary, the CGM has $L'_{\rm CO(4-3)}$/$L'_{\rm CO(1-0)}$ and $L'_{\rm [CI]}$/$L'_{\rm CO(1-0)}$ similar to the ISM of five galaxies in the wider proto-cluster, and its carbon abundance, $X_{\rm [CI]}$/$X_{\rm H2}$, resembles that of the Milky Way and starforming galaxies. The molecular CGM is thus metal-rich and not diffuse, confirming a link between the cold gas and in-situ star formation. Thus, the Spiderweb Galaxy grows not directly through accretion of gas from the cosmic web, but from recycled gas in the GCM.

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arXiv2018

Radio Galaxy Zoo: Compact and extended radio source classification with deep learning

Machine learning techniques have been increasingly useful in astronomical applications over the last few years, for example in the morphological classification of galaxies. Convolutional neural networks have proven to be highly effective in classifying objects in image data. The current work aims to establish when multiple components are present, in the astronomical context of synthesis imaging observations of radio sources. To this effect, we design a convolutional neural network to differentiate between different morphology classes using sources from the Radio Galaxy Zoo (RGZ) citizen science project. In this first step, we focus on exploring the factors that affect the performance of such neural networks, such as the amount of training data, number and nature of layers and the hyperparameters. We begin with a simple experiment in which we only differentiate between two extreme morphologies, using compact and multiple component extended sources. We found that a three convolutional layer architecture yielded very good results, achieving a classification accuracy of 97.4% on a test data set. The same architecture was then tested on a four-class problem where we let the network classify sources into compact and three classes of extended sources, achieving a test achieving a test accuracy of 93.5%. The best-performing convolutional neural network setup has been verified against RGZ Data Release 1 where a final test accuracy of 94.8% was obtained, using both original and augmented images. The use of sigma clipping does not offer a significant benefit overall, except in cases with a small number of training images.

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arXiv2017

Radio Galaxy Zoo: A Search for Hybrid Morphology Radio Galaxies

Hybrid morphology radio sources are a rare type of radio galaxy that display different Fanaroff-Riley classes on opposite sides of their nuclei. To enhance the statistical analysis of hybrid morphology radio sources, we embarked on a large-scale search of these sources within the international citizen science project, Radio Galaxy Zoo (RGZ). Here, we present 25 new candidate hybrid morphology radio galaxies. Our selected candidates are moderate power radio galaxies (L_median = 4.7x10^{24} W/(Hz sr) at redshifts 0.14 1Mpc) radio galaxies, one resides at a centre of a galaxy cluster, and one is hosted by a rare green bean galaxy. Although the origin of the hybrid morphology radio galaxies is still unclear, this type of radio source starts depicting itself as a rather diverse class. We discuss hybrid radio morphology formation in terms of the radio source environment (nurture) and intrinsically occurring phenomena (nature; activity cessation and amplification), showing that these peculiar radio galaxies can be formed by both mechanisms. While high angular resolution follow-up observations are still necessary to confirm our candidates, we demonstrate the efficacy of the Radio Galaxy Zoo in the pre-selection of these sources from all-sky radio surveys, and report the reliability of citizen scientists in identifying and classifying complex radio sources.

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arXiv2017

Deep submillimeter and radio observations in the SSA22 field. I. Powering sources and Lyα escape fraction of Lyα blobs

We study the heating mechanisms and Lyα escape fractions of 35 Lyα blobs (LABs) at z = 3.1 in the SSA22 field. Dust continuum sources have been identified in 11 of the 35 LABs, all with star formation rates (SFRs) above 100 Msun/yr. Likely radio counterparts are detected in 9 out of 29 investigated LABs. The detection of submm dust emission is more linked to the physical size of the Lyα emission than to the Lyα luminosities of the LABs. A radio excess in the submm/radio detected LABs is common, hinting at the presence of active galactic nuclei. Most radio sources without X-ray counterparts are located at the centers of the LABs. However, all X-ray counterparts avoid the central regions. This may be explained by absorption due to exceptionally large column densities along the line-of-sight or by LAB morphologies, which are highly orientation dependent. The median Lyα escape fraction is about 3\% among the submm-detected LABs, which is lower than a lower limit of 11\% for the submm-undetected LABs. We suspect that the large difference is due to the high dust attenuation supported by the large SFRs, the dense large-scale environment as well as large uncertainties in the extinction corrections required to apply when interpreting optical data.

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arXiv2017

Automated Cross-identifying Radio to Infra-red Surveys Using the LRPY Algorithm: A Case Study

Cross-identifying complex radio sources with optical or infra red (IR) counterparts in surveys such as the Australia Telescope Large Area Survey (ATLAS) has traditionally been performed manually. However, with new surveys from the Australian Square Kilometre Array Pathfinder (ASKAP) detecting many tens of million of radio sources such an approach is no longer feasible. This paper presents new software (LRPY - Likelihood Ratio in PYthon) to automate the process of cross-identifying radio sources with catalogues at other wavelengths. LRPY implements the Likelihood Ratio (LR) technique with a modification to account for two galaxies contributing to a sole measured radio component. We demonstrate LRPY by applying it to ATLAS DR3 and a {\it Spitzer}-based multi-wavelength fusion catalogue, identifying 3,848 matched sources via our LR-based selection criteria. A subset of 1987 sources have flux density values for all IRAC bands which allow us to use criteria to distinguish between active galactic nuclei (AGN) and star-forming galaxies (SFG). We find that 936 radio sources ($\approx47\,\%$) meet both of the Lacy and Stern AGN selection criteria. Of the matched sources, 295 have spectroscopic redshifts and we examine the radio to IR flux ratio vs redshift, proposing an AGN selection criterion below the Elvis radio-loud (RL) AGN limit for this dataset. Taking the union of all three AGN selection criteria we identify 956 as AGN ($\approx48\,\%$). From this dataset, we find a decreasing fraction of AGN with lower radio flux densities consistent with other results in the literature.

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arXiv2017

SCORPIO-II: Spectral indices of weak Galactic radio sources

In the next few years the classification of radio sources observed by the large surveys will be a challenging problem, and spectral index is a powerful tool for addressing it. Here we present an algorithm to estimate the spectral index of sources from multiwavelength radio images. We have applied our algorithm to SCORPIO (Umana et al. 2015), a Galactic Plane survey centred around 2.1 GHz carried out with ATCA, and found we can measure reliable spectral indices only for sources stronger than 40 times the rms noise. Above a threshold of 1 mJy, the source density in SCORPIO is 20 percent greater than in a typical extra-galactic field, like ATLAS (Norris et al. 2006), because of the presence of Galactic sources. Among this excess population, 16 sources per square degree have a spectral index of about zero, suggesting optically thin thermal emission such as Hii regions and planetary nebulae, while 12 per square degree present a rising spectrum, suggesting optically thick thermal emission such as stars and UCHii regions.

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arXiv2017

The faint radio sky: VLBA observations of the COSMOS field

We study the faint radio population using wide-field very long baseline interferometry (VLBI) observations of 2865 known radio sources in the Cosmic Evolution Survey (COSMOS) field. The main objective of the project was to determine where active galactic nuclei (AGN) are present. The combination of number of sources, sensitivity, angular resolution and area covered by this project are unprecedented. We have detected 468 radio sources, expected to be AGNs, with the Very Long Baseline Array (VLBA) at 1.4 GHz. This is, to date, the largest sample assembled of VLBI detected sources in the sub-mJy regime. The input sample was taken from previous observations with the Very Large Array (VLA). We present the catalogue with additional multiwavelength information. We find a detection fraction of 20%, considering only those sources from the input catalogue which were in principle detectable with the VLBA (2361). As a function of redshift, we see no evolution of the detection fraction over the redshift range 0.5 1.5 we find that spiral galaxies become the most prevalent (48%). We demonstrate that wide-field VLBI observations, together with new calibration methods such as multi-source self-calibration and mosaicing, result in information which is difficult or impossible to obtain otherwise.

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arXiv2016

Molecular Gas in the Halo Fuels the Growth of a Massive Cluster Galaxy at High Redshift

The largest galaxies in the Universe reside in galaxy clusters. Using sensitive observations of carbon-monoxide, we show that the Spiderweb Galaxy -a massive galaxy in a distant protocluster- is forming from a large reservoir of molecular gas. Most of this molecular gas lies between the protocluster galaxies and has low velocity dispersion, indicating that it is part of an enriched inter-galactic medium. This may constitute the reservoir of gas that fuels the widespread star formation seen in earlier ultraviolet observations of the Spiderweb Galaxy. Our results support the notion that giant galaxies in clusters formed from extended regions of recycled gas at high redshift.

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arXiv2016

Space Telescope and Optical Reverberation Mapping Project VI: reverberating Disk Models for NGC 5548

We conduct a multiwavelength continuum variability study of the Seyfert 1 galaxy NGC 5548 to investigate the temperature structure of its accretion disk. The 19 overlapping continuum light curves (1158 to 9157 angstroms) combine simultaneous HST , Swift , and ground-based observations over a 180 day period from 2014 January to July. Light-curve variability is interpreted as the reverberation response of the accretion disk to irradiation by a central time-varying point source. Our model yields the disk inclination, i, temperature T1 at 1 light day from the black hole, and a temperature-radius slope, alpha. We also infer the driving light curve and find that it correlates poorly with both the hard and soft X-ray light curves, suggesting that the X-rays alone may not drive the ultraviolet and optical variability over the observing period. We also decompose the light curves into bright, faint, and mean accretion-disk spectra. These spectra lie below that expected for a standard blackbody accretion disk accreting at L/LEdd = 0.1

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arXiv2016

The radio spectral energy distribution of infrared-faint radio sources

Infrared-faint radio sources (IFRS) are a class of radio-loud (RL) active galactic nuclei (AGN) at high redshifts (z > 1.7) that are characterised by their relative infrared faintness, resulting in enormous radio-to-infrared flux density ratios of up to several thousand. We aim to test the hypothesis that IFRS are young AGN, particularly GHz peaked-spectrum (GPS) and compact steep-spectrum (CSS) sources that have a low frequency turnover. We use the rich radio data set available for the Australia Telescope Large Area Survey fields, covering the frequency range between 150 MHz and 34 GHz with up to 19 wavebands from different telescopes, and build radio spectral energy distributions (SEDs) for 34 IFRS. We then study the radio properties of this class of object with respect to turnover, spectral index, and behaviour towards higher frequencies. We also present the highest-frequency radio observations of an IFRS, observed with the Plateau de Bure Interferometer at 105 GHz, and model the multi-wavelength and radio-far-infrared SED of this source. We find IFRS usually follow single power laws down to observed frequencies of around 150 MHz. Mostly, the radio SEDs are steep, but we also find ultra-steep SEDs. In particular, IFRS show statistically significantly steeper radio SEDs than the broader RL AGN population. Our analysis reveals that the fractions of GPS and CSS sources in the population of IFRS are consistent with the fractions in the broader RL AGN population. We find that at least 18% of IFRS contain young AGN, although the fraction might be significantly higher as suggested by the steep SEDs and the compact morphology of IFRS. The detailed multi-wavelength SED modelling of one IFRS shows that it is different from ordinary AGN, although it is consistent with a composite starburst-AGN model with a star formation rate of 170 solar masses per year.

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arXiv2016

Radio Galaxy Zoo: discovery of a poor cluster through a giant wide-angle tail radio galaxy

We have discovered a previously unreported poor cluster of galaxies (RGZ-CL J0823.2+0333) through an unusual giant wide-angle tail radio galaxy found in the Radio Galaxy Zoo project. We obtained a spectroscopic redshift of $z=0.0897$ for the E0-type host galaxy, 2MASX J08231289+0333016, leading to M$_r = -22.6$ and a $1.4\,$GHz radio luminosity density of $L_{\rm 1.4} = 5.5\times10^{24}$ W Hz$^{-1}$. These radio and optical luminosities are typical for wide-angle tailed radio galaxies near the borderline between Fanaroff-Riley (FR) classes I and II. The projected largest angular size of $\approx8\,$arcmin corresponds to $800\,$kpc and the full length of the source along the curved jets/trails is $1.1\,$Mpc in projection. X-ray data from the XMM-Newton archive yield an upper limit on the X-ray luminosity of the thermal emission surrounding RGZ J082312.9+033301,at $1.2-2.6\times10^{43}$ erg s$^{-1}$ for assumed intra-cluster medium temperatures of $1.0-5.0\,$keV. Our analysis of the environment surrounding RGZ J082312.9+033301 indicates that RGZ J082312.9+033301 lies within a poor cluster. The observed radio morphology suggests that (a) the host galaxy is moving at a significant velocity with respect to an ambient medium like that of at least a poor cluster, and that (b) the source may have had two ignition events of the active galactic nucleus with $10^7\,$yrs in between. This reinforces the idea that an association between RGZ J082312.9+033301, and the newly discovered poor cluster exists.

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arXiv2016

Automated detection of extended sources in radio maps: progress from the SCORPIO survey

Automated source extraction and parameterization represents a crucial challenge for the next-generation radio interferometer surveys, such as those performed with the Square Kilometre Array (SKA) and its precursors. In this paper we present a new algorithm, dubbed CAESAR (Compact And Extended Source Automated Recognition), to detect and parametrize extended sources in radio interferometric maps. It is based on a pre-filtering stage, allowing image denoising, compact source suppression and enhancement of diffuse emission, followed by an adaptive superpixel clustering stage for final source segmentation. A parameterization stage provides source flux information and a wide range of morphology estimators for post-processing analysis. We developed CAESAR in a modular software library, including also different methods for local background estimation and image filtering, along with alternative algorithms for both compact and diffuse source extraction. The method was applied to real radio continuum data collected at the Australian Telescope Compact Array (ATCA) within the SCORPIO project, a pathfinder of the ASKAP-EMU survey. The source reconstruction capabilities were studied over different test fields in the presence of compact sources, imaging artefacts and diffuse emission from the Galactic plane and compared with existing algorithms. When compared to a human-driven analysis, the designed algorithm was found capable of detecting known target sources and regions of diffuse emission, outperforming alternative approaches over the considered fields.

astro-ph.IM↗