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

Unveiling the rarest morphologies of the LOFAR Two-metre Sky Survey radio source population with self-organised maps

Context. The Low Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) is a low-frequency radiocontinuum survey of the Northern sky at an unparalleled resolution and sensitivity. Aims. In order to fully exploit this huge dataset and those produced by the Square Kilometre Array in the next decade, automated methods in machine learning and data-mining will be increasingly essential both for morphological classifications and for identifying optical counterparts to the radio sources. Methods. Using self-organising maps (SOMs), a form of unsupervised machine learning, we created a dimensionality reduction of the radio morphologies for the ∼25k extended radio continuum sources in the LoTSS first data release, which is only ∼2 percent of the final LoTSS survey. We made use of PINK, a code which extends the SOM algorithm with rotation and flipping invariance, increasing its suitability and effectiveness for training on astronomical sources. Results. After training, the SOMs can be used for a wide range of science exploitation and we present an illustration of their potential by finding an arbitrary number of morphologically rare sources in our training data (424 square degrees) and subsequently in an area of the sky (∼5300 square degrees) outside the trainingdata. Objects found in this way span a wide range of morphological and physical categories: extended jets of radio active galactic nuclei, diffuse cluster haloes and relics, and nearby spiral galaxies. Finally, to enable accessible, interactive, and intuitive data exploration, we showcase the LOFAR-PyBDSF Visualisation Tool, which allows users to explore the LoTSS dataset through the trained SOMs

Radio Galaxy Zoo: host galaxies and radio morphologies derived from visual inspection

We present results from the first 12 months of operation of Radio Galaxy Zoo, which upon completion will enable visual inspection of over 170000 radio sources to determine the host galaxy of the radio emission and the radio morphology. Radio Galaxy Zoo uses 1.4 GHz radio images from both the Faint Images of the Radio Sky at Twenty Centimeters (FIRST) and the Australia Telescope Large Area Survey (ATLAS) in combination with mid-infrared images at 3.4 μm from the Wide-field Infrared Survey Explorer (WISE) and at 3.6 μm from the Spitzer Space Telescope. We present the early analysis of the WISE mid-infrared colours of the host galaxies. For images in which there is >75 per cent consensus among the Radio Galaxy Zoo cross-identifications, the project participants are as effective as the science experts at identifying the host galaxies. The majority of the identified host galaxies reside in the mid-infrared colour space dominated by elliptical galaxies, quasi-stellar objects and luminous infrared radio galaxies. We also find a distinct population of Radio Galaxy Zoo host galaxies residing in a redder mid-infrared colour space consisting of star-forming galaxies and/or dust-enhanced non-star-forming galaxies consistent with a scenario of merger-driven active galactic nuclei (AGN) formation. The completion of the full Radio Galaxy Zoo project will measure the relative populations of these hosts as a function of radio morphology and power while providing an avenue for the identification of rare and extreme radio structures. Currently, we are investigating candidates for radio galaxies with extreme morphologies, such as giant radio galaxies, late-type host galaxies with extended radio emission and hybrid morphology radio source

Radio Galaxy Zoo:host galaxies and radio morphologies derived from visual inspection

We present results from the first 12 months of operation of Radio Galaxy Zoo, which upon completion will enable visual inspection of over 170 000 radio sources to determine the host galaxy of the radio emission and the radio morphology. Radio Galaxy Zoo uses 1.4 GHz radio images from both the Faint Images of the Radio Sky at Twenty Centimeters (FIRST) and the Australia Telescope Large Area Survey (ATLAS) in combination with mid-infrared images at 3.4 μm from the Wide-field Infrared Survey Explorer (WISE) and at 3.6 μm from the Spitzer Space Telescope. We present the early analysis of the WISE mid-infrared colours of the host galaxies. For images in which there is >75 per cent consensus among the Radio Galaxy Zoo cross-identifications, the project participants are as effective as the science experts at identifying the host galaxies. The majority of the identified host galaxies reside in the mid-infrared colour space dominated by elliptical galaxies, quasi-stellar objects and luminous infrared radio galaxies. We also find a distinct population of Radio Galaxy Zoo host galaxies residing in a redder mid-infrared colour space consisting of star-forming galaxies and/or dust-enhanced non-star-forming galaxies consistent with a scenario of merger-driven active galactic nuclei (AGN) formation. The completion of the full Radio Galaxy Zoo project will measure the relative populations of these hosts as a function of radio morphology and power while providing an avenue for the identification of rare and extreme radio structures. Currently, we are investigating candidates for radio galaxies with extreme morphologies, such as giant radio galaxies, late-type host galaxies with extended radio emission and hybrid morphology radio sources

Infrared Narrow-Band Tomography of the Local Starburst NGC 1569 with LBT/LUCIFER

We used the near-IR imager/spectrograph LUCIFER mounted on the Large Binocular Telescope (LBT) to image, with sub-arcsec seeing, the local dwarf starburst NGC 1569 in the JHK bands and HeI 1.08 micron, [FeII] 1.64 micron and Brgamma narrow-band filters. We obtained high-quality spatial maps of HeI, [FeII] and Brgamma emission across the galaxy, and used them together with HST/ACS images of NGC 1569 in the Halpha filter to derive the two-dimensional spatial map of the dust extinction and surface star formation rate density. We show that dust extinction is rather patchy and, on average, higher in the North-West (NW) portion of the galaxy [E_g(B-V) = 0.71 mag] than in the South-East [E_g(B-V) = 0.57 mag]. Similarly, the surface density of star formation rate peaks in the NW region of NGC 1569, reaching a value of about 4 x 10^-6 M_sun yr^-1 pc^-2. The total star formation rate as estimated from the integrated, dereddened Halpha luminosity is about 0.4 M_sun yr^-1, and the total supernova rate from the integrated, dereddened [FeII] luminosity is about 0.005 yr^-1 (assuming a distance of 3.36 Mpc). The azimuthally averaged [FeII]/Brgamma flux ratio is larger at the edges of the central, gas-deficient cavities (encompassing the super star clusters A and B) and in the galaxy outskirts. If we interpret this line ratio as the ratio between the average past star formation (as traced by supernovae) and on-going activity (represented by OB stars able to ionize the interstellar medium), it would then indicate that star formation has been quenched within the central cavities and lately triggered in a ring around them. The number of ionizing hydrogen and helium photons as computed from the integrated, dereddened Halpha and HeI luminosities suggests that the latest burst of star formation occurred about 4 Myr ago and produced new stars with a total mass of ~1.8 x 10^6 M_sun. [Abridged]Comment: accepted for publication in A

A Gaussian process cross-correlation approach to time-delay estimation in active galactic nuclei

Context. We present a probabilistic cross-correlation approach to estimate time delays in the context of reverberation mapping (RM) of active galactic nuclei (AGN). Aims. We reformulate the traditional interpolated cross-correlation method as a statistically principled model that delivers a posterior distribution for the delay. Methods. The method employs Gaussian processes as a model for observed AGN light curves. We describe the mathematical formalism and demonstrate the new approach using both simulated light curves and available RM observations. Results. The proposed method delivers a posterior distribution for the delay that accounts for observational noise and the non-uniform sampling of the light curves. This feature allows us to fully quantify the uncertainty on the delay and propagate it to subsequent calculations of dependant physical quantities, such as black hole masses. The method delivers out-of-sample predictions, which enables us to subject it to model selection, and can calculate the joint posterior delay for more than two light curves. Conclusions. Because of the numerous advantages of our reformulation and the simplicity of its application, we anticipate that our method will find favour not only in the specialised community of RM, but also in all fields where cross-correlation analysis is performed. We provide the algorithms and examples of their application as part of our Julia GPCC package

Disentangling the optical AGN and host-galaxy luminosity with a probabilistic flux variation gradient

Context. We present a novel probabilistic flux variation gradient (PFVG) approach to separate the contributions of active galactic nuclei (AGN) and host galaxies in the context of photometric reverberation mapping (PRM) of AGN. Aims. We explored the ability of recovering the fractional contribution in a model-independent way using the entire set of light curves obtained through different filters and photometric apertures simultaneously. Methods. The method is based on the observed “bluer when brighter” phenomenon that is attributed to the superimposition of a two-component structure; the red host galaxy, which is constant in time, and the varying blue AGN. We describe the PFVG mathematical formalism and demonstrate its performance using simulated light curves and available PRM observations. Results. The new probabilistic approach is able to recover host-galaxy fluxes to within 1% precision as long as the light curves do not show a significant contribution from time delays. This represents a significant improvement with respect to previous applications of the traditional FVG method to PRM data. Conclusions. The proposed PFVG provides an efficient and accurate way to separate the AGN and host-galaxy luminosities in PRM monitoring data. The method will be especially helpful in the case of large upcoming photometric survey telescopes such as the public optical/near-infrared Legacy Survey of Space and Time (LSST) at the Vera C. Rubin Observatory. Finally, we have made the algorithms freely available as part of our Julia PFVG package