相关论文: A novel approach to identify blazar emission state…

We carry out a classification of the observed pulsar dataset into distinct clusters, based on the $P-\dot{P}$ diagram, using Extreme Deconvolution based Gaussian Mixture Model. We then use the Bayesian Information Criterion to select the…

The changing-look blazars (CLBs) are the blazars that their optical spectral lines at different epochs show a significant changes and present a clear transition between the standard FSRQ and BL Lac types. The changing-look phenomena in…

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 present a comprehensive temporal and spectral analysis of a few blazars using multi-wavelength observations. Rapid flux variations are quantified via the doubling/halving timescale method, revealing the shortest variability timescales of…

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…

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…

We have recently proposed a simplified scenario for blazars in which these sources are classified as flat-spectrum radio quasars or BL Lacs according to the prescriptions of unified schemes, and to a varying combination of Doppler boosted…

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…

Based on the collected multiwavelength data, namely in the radio (NVSS, FIRST, RATAN-600), IR (WISE), optical (Pan-STARRS), UV (GALEX), and X-ray (ROSAT, Swift-XRT) ranges, we have performed a cluster analysis for the blazars of the…

The time evolution of the electromagnetic emission from blazars, in particular high frequency peaked sources (HBLs), displays irregular activity not yet understood. In this work we report a methodology capable of characterizing the time…

Blazars dominate the extragalactic $\gamma$-ray sky and show pronounced flares. Using public Fermi-LAT light curves for 732 blazars with secure redshifts, I implement an automated pipeline to identify and characterize $\gamma$-ray bursts…

Since mid-2007 we have carried out a dedicated long-term monitoring programme at 15 GHz using the Owens Valley Radio Observatory 40 meter telescope. One of the main goals of this programme is to study the relation between the radio and…

Blazars are known to show periods of quiescence followed by outbursts visible throughout the electromagnetic spectrum. We present a novel maximum likelihood approach to capture this bimodal behavior by examining blazar radio variability 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…

We are leading a comprehensive multi-waveband monitoring program of 34 gamma-ray bright blazars designed to locate the emission regions of blazars from radio to gamma-ray frequencies. The "maps" are anchored by sequences of images in both…

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)…

In this work, a time-dependent modeling is developed to study the emission properties of blazars in the low state. Motivated by various observations, we speculate and assume that numerous discrete radiation zones throughout the jet of a…

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…

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…