相关论文: DRAGNs in the Forest: Identifying Artifacts with R…

Active Galactic Nuclei (AGN) can often be identified in radio images as two lobes, sometimes connected to a core by a radio jet. This multi-component morphology unfortunately creates difficulties for source-finders, leading to components…

We present a systematic search for radio active galactic nuclei (AGNs) in dwarf galaxies using recent observations taken by the Very Large Array Sky Survey (VLASS). To select these objects, we first establish a criterion to identify…

We present a catalogue of 3557 Double Radio sources associated with Active Galactic Nuclei (DRAGNs) from the First Pilot Survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array…

Blazars are radio-loud Active Galactic Nuclei (AGN) whose jets have a very small angle to our line of sight. Observationally, the radio emission are mostly compact or a compact-core with a 1-sided jet. With 2.5$^{\prime\prime}$ resolution…

Radio loud active galactic nuclei (RLAGNs) are often morphologically complex objects that can consist of multiple, spatially separated, components. Astronomers often rely on visual inspection to resolve radio component association. However,…

Modern image generators produce strikingly realistic images, where only artifacts like distorted hands or warped objects reveal their synthetic origin. Detecting these artifacts is essential: without detection, we cannot benchmark…

The Very Large Array Sky Survey (VLASS) is observing the entire sky north of $-40^{\circ}$ in the S-band ($2<\nu<4\,$GHz), with the highest angular resolution ($2''.5$) of any all-sky radio continuum survey to date. VLASS will cover its…

Remnant radio galaxies represent the dying phase of radio-loud active galactic nuclei (AGN). Large samples of remnant radio galaxies are important for quantifying the radio galaxy life cycle. The remnants of radio-loud AGN can be identified…

Humans are able to categorize images very efficiently, in particular to detect the presence of an animal very quickly. Recently, deep learning algorithms based on convolutional neural networks (CNNs) have achieved higher than human accuracy…

We present a wide-area and deep optical identification catalog for radio sources based on the VLASS Epoch 2 catalog at 3 GHz. Optical counterparts are identified using the final-year internal processing of the Hyper Suprime-Cam Subaru…

This whitepaper describes how the VLASS could be designed in a manner to allow the identification of candidate dual active galactic nuclei (AGN) at separations <7 kpc. Dual AGN represent a clear marker of two supermassive black holes within…

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 -…

The ability to automatically classify source code repositories with ''topics'' that reflect their content and purpose is very useful, especially when navigating or searching through large software collections. However, existing approaches…

We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that…

Context. Active galactic nuclei (AGNs) and star forming galaxies (SFGs) are the primary sources of extragalactic radio sky. But it is difficult to distinguish the radio emission produced by AGNs from that by SFGs, especially when the radio…

Novel techniques are indispensable to process the flood of data from the new generation of radio telescopes. In particular, the classification of astronomical sources in images is challenging. Morphological classification of radio galaxies…

Radio galaxies can extend far beyond the stellar component of their originating host galaxies, and their radio emission can consist of multiple discrete components. Furthermore, the apparent source structure will depend on survey…

Radio observations of strongly lensed objects are valuable as cosmological probes. Lensed radio sources have proven difficult to identify in large part due to the limited depth and angular resolution of the previous generation of radio sky…

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…

Context. A defining characteristic of active galactic nuclei (AGN) that distinguishes them from other astronomical sources is their stochastic variability, which is observable across the entire electromagnetic spectrum. Upcoming optical…