Related papers: Efficient Fermi Source Identification with Machine…
Classification will be an important first step for upcoming surveys that will detect billions of new sources such as LSST and Euclid, as well as DESI, 4MOST and MOONS. The application of traditional methods of model fitting and…
Active Galactic Nuclei (AGNs) are characterized by strong temporal flux density variability across the electromagnetic spectrum, offering insights into the complex physical processes governing accretion and plasma outflows. To…
The third Fermi Large Area Telescope (LAT) $\gamma$-ray source catalog (3FGL) contains over 1000 objects for which there is no known counterpart at other wavelengths. The physical origin of the $\gamma$-ray emission of those objects is…
The paper investigates nonlinear system identification using system output data at various linearized operating points. A feed-forward multi-layer Artificial Neural Network (ANN) based approach is used for this purpose and tested for two…
Distinguishing active galaxies from star-forming galaxies is essential for understanding galaxy evolution. Diagnostic methods like the BPT (Baldwin, Phillips, and Terlevich) diagram use optical emission-line ratios to separate galaxies.…
We present the results of an all-sky radio survey between 5 and 9 GHz of the fields surrounding all unassociated gamma-ray objects listed in the Fermi Large Area Telescope Second Source Catalog (2FGL). The goal of these observations is to…
Nowadays, Machine Learning techniques offer fast and efficient solutions for classification problems that would require intensive computational resources via traditional methods. We examine the use of a supervised Random Forest to classify…
Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks. Techniques without ML have also been evaluated and are included for comparison. The…
With the advent of next-generation surveys and the expectation of discovering huge numbers of strong gravitational lens systems, much effort is being invested into developing automated procedures for handling the data. The several orders of…
We proposed a machine learning approach to identify and distinguish dusty stellar sources employing supervised and unsupervised methods and categorizing point sources, mainly evolved stars, using photometric and spectroscopic data collected…
An incremental version of the fourth catalog of active galactic nuclei (AGNs) detected by the Fermi-Large Area Telescope is presented. This version (4LAC-DR3) derives from the third data release of the 4FGL catalog based on 12 years of E>50…
Despite the large number of discoveries made recently by Fermi, the origins of the so called unidentified gamma-ray sources remain unknown. The large number of these sources suggests that among them there could be a population that…
In chemistry tabulations and Flamelet combustion models, the Flamelet Generated Manifold (FGM) is recognized for its precision and physical representation. The practical implementation of FGM requires a significant allocation of memory…
We identified Active Galactic Nuclei (AGN) candidates as counterparts to unidentified gamma-ray sources (UGS) from the Fermi-LAT Fourth Source Catalogue at lower Galactic latitudes. Our methodology is based on the use of near- and…
The determination of distance is fundamental in astrophysics. Gamma-ray sources are poorly characterized in this sense, as the limited angular resolution and poor photon-count statistics in gamma-ray astronomy makes it difficult to…
We present a new and efficient algorithm for finding point sources in the photon event data stream from the Fermi Gamma-Ray Space Telescope, FermiFAST. The key advantage of FermiFAST is that it constructs a catalogue of potential sources…
With fault-tolerant quantum computing on the horizon, there is growing interest in applying quantum computational methods to data-intensive scientific fields like remote sensing. Quantum machine learning (QML) has already demonstrated…
We investigate the spectroscopic optical properties of gamma-ray sources detected with high significance above 50 GeV in the Third Catalog of Hard Fermi-LAT Sources (3FHL) and that are good candidates as TeV emitters. We focus on the 91…
The latest source catalog of the Fermi-LAT telescope contains more than 7000 $\gamma$-ray sources at GeV energies, with the two dominant source classes thought to be blazars and rotation-powered pulsars. Our target is the identification of…
The high-frequency radio sky, like the gamma-ray sky surveyed by the Fermi satellite, is dominated by flat spectrum radio quasars and BL Lac objects at bright flux levels. To investigate the relationship between radio and gamma-ray emission…