相关论文: Deep Learning Blazar Classification based on Multi…
Machine learning has emerged as a powerful tool in the field of gamma-ray astrophysics. The algorithms can distinguish between different source types, such as blazars and pulsars, and help uncover new insights into the high-energy universe.…
Blazars are a remarkable type of Active Galactic Nuclei (AGN) that are playing an important and rapidly growing role in today's multi-frequency and multi-messenger astrophysics. In the past several years, blazars have been discovered in…
The Fermi Large Area Telescope (Fermi-LAT) has detected more than 7,000 gamma-ray sources, a significant fraction of which are identified as blazars, while a comparable number remain classified as blazars of uncertain type (BCUs) or are…
Blazars are a highly-variable, radio-loud subclass of active galactic nuclei (AGN). In order to better understand such objects we must be able to easily identify candidate blazars from the growing population of unidentified sources. Working…
Interpreting the spectral energy distributions (SEDs) of astrophysical objects with physically motivated models is computationally expensive. These models require solving coupled differential equations in high-dimensional parameter spaces,…
Blazars are a subclass of active galactic nuclei with relativistic jets pointing toward the observer. They are notable for their flux variability at all observed wavelengths and timescales. Together with simultaneous measurements at lower…
Context: Being dominated by non-thermal emission from aligned relativistic jets, blazars allow us to elucidate the physics of extragalactic jets, and, ltimately, how the energy is extracted from the central black hole in radio-loud active…
Machine learning based approaches are emerging as very powerful tools for many applications including source classification in astrophysics research due to the availability of huge high quality data from different surveys in observational…
The study of machine learning (ML) techniques for the autonomous classification of astrophysical sources is of great interest, and we explore its applications in the context of a multifrequency data-frame. We test the use of supervised ML…
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…
Context:Blazars are the rarest and most powerful active galactic nuclei, playing a crucial and growing role in today multi-frequency and multi-messenger astrophysics. Current blazar catalogs, however, are incomplete and particularly…
Blazars are active galactic nuclei with relativistic jets pointed almost directly at Earth. Blazars are characterized by strong, apparently stochastic flux variability at virtually all observed wavelengths and timescales, from minutes to…
Active Galaxies with a jet pointing towards us, so-called blazars, play an important role in the field of high-energy astrophysics. One of the most important features in the classification scheme of blazars is the peak frequency of the…
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…
We analyse 77 \textit{Fermi} sources and their potential low-energy counterparts previously proposed in the literature. These sources were classified as active galactic nuclei, mainly blazars, based on optical spectroscopy. The main goals…
Blazars, a highly energetic subclass of jetted active galactic nuclei, show a broad band spectral energy distribution (SED) with two bumps, resulting from non-thermal jet emission. In 1998, an anticorrelation between the SED luminosity and…
Blazars are currently separated into BL Lacertae objects (BL Lacs) and flat spectrum radio quasars (FSRQ) based on the strength of their emission lines. This is done rather arbitrarily by defining a diagonal line in the Ca H&K break value…
Blazars are very broadband cosmic sources with spectra spanning over twenty orders of magnitude in frequency, down to the 100 MHz regime in the radio range, up to VHE at several tens of TeV. The modelling of their spectral energy…
Blazars are the brightest and most abundant persistent sources in the extragalactic gamma-ray sky. Due to their significance, they are often observed across various energy bands to explore potential correlations between emissions at…
Machine learning (ML) and deep learning (DL) techniques are increasingly used across astrophysics, enabled by the growing availability of data and improved acquisition methods. These approaches now support tasks from redshift estimation to…