Related papers: Data-Efficient Classification of Radio Galaxies
Aims. This work investigates the potential of using the wavelength-dependence of galaxy structural parameters (S\'ersic index, n, and effective radius, Re) to separate galaxies into distinct types. Methods. A sample of nearby galaxies with…
The ring structures of disk galaxies are vital for understanding galaxy evolution and dynamics. However, due to the scarcity of ringed galaxies and challenges in their identification, traditional methods often struggle to efficiently obtain…
Galaxy morphologies provide valuable insights into their formation processes, tracing the spatial distribution of ongoing star formation and encoding signatures of dynamical interactions. While such information has been extensively…
In this work we simulate the $50-200$ MHz radio sky that is constrained in the field of view ($5^{\circ}$ radius) of the 21 Centimeter Array (21CMA), by carrying out Monte-Carlo simulations to model redshifted cosmological reionization…
Radio propagation modeling and prediction is fundamental for modern cellular network planning and optimization. Conventional radio propagation models fall into two categories. Empirical models, based on coarse statistics, are simple and…
Detecting diffuse radio emission, such as from halos, in galaxy clusters is crucial for understanding large-scale structure formation in the universe. Traditional methods, which rely on X-ray and Sunyaev-Zeldovich (SZ) cluster…
We present a novel approach for classifying stars as binary or exoplanet using deep learning techniques. Our method utilizes feature extraction, wavelet transformation, and a neural network on the light curves of stars to achieve…
The formation and evolution of ring structures in galaxies are crucial for understanding the nature and distribution of dark matter, galactic interactions, and the internal secular evolution of galaxies. However, the limited number of…
Correlations between jet power and active time for z < 0.1 high excitation and low excitation radio galaxies are explored as well as evidence in favor of a specific, non-random distribution for these objects including mid-infrared emitting…
Context. The accurate classification of hundreds of thousands of galaxies observed in modern deep surveys is imperative if we want to understand the universe and its evolution. Aims. Here, we report the use of machine learning techniques to…
The forthcoming generation of radio telescope arrays promises significant advancements in sensitivity and resolution, enabling the identification and characterization of many new faint and diffuse radio sources. Conventional manual…
Despite the plethora of deep (sub-mJy) radio surveys there remains considerable doubt as to the exact nature of the galaxies contributing to the source counts. Current evidence suggests that starformation in moderately luminous 'normal'…
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…
Neural network (NN) based methods are applied to the detection of radio frequency interference (RFI) in post-correlation,post-calibration time/frequency data. While calibration doesaffect RFI for the sake of this work a reduced dataset…
There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a…
The faint radio-source population includes sources dominated both by star formation and active galactic nuclei (AGN), encoding the evolution of activity in the Universe. To investigate its nature, we probabilistically classified 4,471 radio…
We explore the use of different radio galaxy populations as tracers of different mass halos and therefore, with different bias properties, to constrain primordial non-Gaussianity of the local type. We perform a Fisher matrix analysis based…
The idea that mergers are more likely in dense groups or clusters coupled with the assumption that such events lead to cold gas flows onto black holes, suggests a direct relationship between the radiative efficiency of an active galactic…
There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a…
Context: The huge and still rapidly growing amount of galaxies in modern sky surveys raises the need of an automated and objective classification method. Unsupervised learning algorithms are of particular interest, since they discover…