Related papers: A machine learning classifier for LOFAR radio gala…
Radio galaxies exhibit a rich diversity of characteristics and emit radio emissions through a variety of radiation mechanisms, making their classification into distinct types based on morphology a complex challenge. To address this…
Machine learning is an automatic technique that is revolutionizing scientific research, with innovative applications and wide use in astrophysics. The aim of this study was to developed an optimized version of an Artificial Neural Network…
Radio galaxies are linearly polarized -- an important property that allows us to infer the properties of the magnetic field of the source and its environment. However at low frequencies, Faraday rotation substantially depolarizes the…
In this work we study the flux density dependence of the redshift distribution of low-frequency radio sources observed in the LOFAR Two-metre Sky Survey (LoTSS) deep fields and apply it to estimate the clustering length of the large-scale…
We conduct X-ray spectral fits on 184 likely counterparts to Fermi-LAT 3FGL unassociated sources. Characterization and classification of these sources allows for more complete population studies of the high-energy sky. Most of these X-ray…
The new generation of broad-band radio continuum surveys will provide large data sets with polarization information. New algorithms need to be developed to extract reliable catalogs of linearly polarized sources that can be used to…
We have conducted a deep survey (with a central rms of $55\mu\textrm{Jy}$) with the LOw Frequency ARray (LOFAR) at 120-168 MHz of the Bo\"otes field, with an angular resolution of $3.98^{''}\times6.45^{''}$, and obtained a sample of 10091…
With the advent of new generation low-frequency telescopes, such as the LOw Frequency ARray (LOFAR), and improved calibration techniques, we have now started to unveil the sub GHz radio sky with unprecedented depth and sensitivity. The…
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…
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…
Searching for as yet undetected gamma-ray sources is a major target of the Fermi LAT Collaboration. We present an algorithm capable of identifying such type of sources by non-parametrically clustering the directions of arrival of the…
In this data release from the LOFAR Two-metre Sky Survey (LoTSS) we present 120-168MHz images covering 27% of the northern sky. Our coverage is split into two regions centred at approximately 12h45m +44$^\circ$30' and 1h00m +28$^\circ$00'…
The rate of image acquisition in modern synoptic imaging surveys has already begun to outpace the feasibility of keeping astronomers in the real-time discovery and classification loop. Here we present the inner workings of a framework,…
With the arrival of a number of wide-field snapshot image-plane radio transient surveys, there will be a huge influx of images in the coming years making it impossible to manually analyse the datasets. Automated pipelines to process the…
The relative positions of the high and low surface brightness regions of radio-loud active galaxies in the 3CR sample were found by Fanaroff and Riley to be correlated with their luminosity. We revisit this canonical relationship with a…
The new generation of high-resolution broad-band radio telescopes, like the Low Frequency Array (LOFAR), produces, depending on the level of compression, between 1 to 10 TB of data per hour after correlation. Such a large amount of…
The present generation of weak lensing surveys will be superseded by surveys run from space with much better sky coverage and high level of signal to noise ratio, such as SNAP. However, removal of any systematics or noise will remain a…
The WISE satellite has detected hundreds of millions sources over the entire sky. Classifying them reliably is however a challenging task due to degeneracies in WISE multicolour space and low levels of detection in its two…
The study of transient and variable low-frequency radio sources is a key goal for LOFAR, with an extremely broad science case ranging from relativistic jets sources to pulsars, exoplanets, radio bursts at cosmological distances, the…
Classification of young stellar objects (YSOs) into different evolutionary stages helps us to understand the formation process of new stars and planetary systems. Such classification has traditionally been based on spectral energy…