Related papers: Hunting for the candidates of misclassified source…
We utilize machine learning methods to distinguish BL Lacertae objects (BL Lac) from Flat Spectrum Radio Quasars (FSRQ) within a sample of likely X-ray blazar counterparts to Fermi 3FGL unassociated gamma-ray sources. From our previous…
The Fermi Large Area Telescope (LAT) has detected more than 5000 gamma-ray sources in its first 8 years of operation. More than 3000 of them are blazars. About 60 per cent of the Fermi-LAT blazars are classified as BL Lacertae objects (BL…
The Fermi fourth catalog of active galactic nuclei (AGNs) data release 3 (4LAC-DR3) contains 3407 AGNs, out of which 755 are flat spectrum radio quasars (FSRQs), 1379 are BL Lacertae objects (BL Lacs), 1208 are blazars of unknown (BCUs)…
The deepest all-sky survey available in the $\gamma$-ray band - the last release of the Fermi-LAT catalogue (4FGL-DR3) based on the data accumulated in 12 years, contains more than 6600 sources. The largest population among the sources is…
The recently published fourth Fermi Large Area Telescope source catalog (4FGL) reports 5065 gamma-ray sources in terms of direct observational gamma-ray properties. Among the sources, the largest population is the Active Galactic Nuclei…
Among the ~2157 unassociated sources in the third data release (DR3) of the fourth Fermi catalog, ~1200 were observed with the Neil Gehrels Swift Observatory pointed instruments. These observations yielded 238 high S/N X-ray sources within…
Significant progress in the classification of Fermi unassociated sources , has led to an increasing number of blazars are being found. The optical spectrum is effectively used to classify the blazars into two groups such as BL Lacs and flat…
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…
In the third catalog of active galactic nuclei detected by the Fermi-LAT (3LAC) Clean Sample, there are 402 blazars candidates of uncertain type (BCU). Due to the limitations of astronomical observation or intrinsic properties, it is…
In the third catalog of active galactic nuclei detected by the $Fermi$ Large Area Telescope Clean (3LAC) sample, there are 402 blazars candidates of uncertain type (BCU). The proposed analysis will help to evaluate the potential optical…
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…
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.…
We aim to test if a blazar candidate of uncertain-type (BCU) in the third Fermi active galactic nuclei catalog (3LAC) can be potentially classified as a BL Lac object or a flat spectrum radio quasar (FSRQ) by performing a statistical…
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 show that a blazar classification in BL Lacs and Flat Spectrum Radio Quasars may not be adequate when it relies solely on the equivalent widths (EWs) of optical lines. In fact, depending on redshift, some strong emission lines can fall…
In this study, we analyze the $\sim 16$ yr Fermi-LAT data of 160 blazars consisting of 92 flat-spectrum radio quasars (FSRQs), 64 BL Lacertae type objects (BL Lacs), and 4 blazar candidates of unknown type objects (BCU), and exhibit their…
In this work, the support vector machine (SVM) method is adopted to separate BL Lacertae objects (BL Lacs) and flat spectrum radio quasars (FSRQs) in the plots of photon spectrum index against the photon flux, $\alpha_{\rm ph} \sim {\rm…
In the recently published 3FGL catalogue, the Fermi/LAT collaboration reports the detection of $\gamma$-ray emission from 3034 sources obtained after four years of observations. The nature of 1010 of those sources is unknown, whereas 2023…
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…
We present simultaneous Planck, Swift, Fermi, and ground-based data for 105 blazars belonging to three samples with flux limits in the soft X-ray, hard X-ray, and gamma-ray bands. Our unique data set has allowed us to demonstrate that the…