Blazar Flaring Patterns (B-FlaP): Classifying Blazar Candidates of Uncertain type in the third Fermi-LAT catalog by Artificial Neural Networks

Abstract

The Fermi Large Area Telescope (LAT) is currently the most important facility for investigating the GeV $\gamma$-ray sky. With Fermi LAT more than three thousand $\gamma$-ray sources have been discovered so far. 1144 ($\sim 40\%$) of the sources are active galaxies of the blazar class, and 573 ($\sim 20\%$) are listed as Blazar Candidate of Uncertain type (BCU), or sources without a conclusive classification. We use the Empirical Cumulative Distribution Functions (ECDF) and the Artificial Neural Networks (ANN) for a fast method of screening and classification for BCUs based on data collected at $\gamma$-ray energies only, when rigorous multiwavelength analysis is not available. Based on our method, we classify 342 BCUs as BL Lacs and 154 as FSRQs, while 77 objects remain uncertain. Moreover, radio analysis and direct observations in ground-based optical observatories are used as counterparts to the statistical classifications to validate the method. This approach is of interest because of the increasing number of unclassified sources in Fermi catalogs and because blazars and in particular their subclass High Synchrotron Peak (HSP) objects are the main targets of atmospheric Cherenkov telescopes.

arXiv comment18 pages, 17 figures, accepted for publication on MNRAS

References in corpus (23)

• The Large Area Telescope on the Fermi Gamma-ray Space Telescope Mission
• The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III
• The 6dF Galaxy Survey: Final Redshift Release (DR3) and Southern Large-Scale Structures
• The Spectral Energy Distribution of Fermi bright blazars
• The Second Catalog of Active Galactic Nuclei Detected by the Fermi Large Area Telescope
• The 6dF Galaxy Survey: Samples, Observational Techniques and the First Data Release
• The Third Catalog of Active Galactic Nuclei Detected by the Fermi Large Area Telescope
• SUMSS: A Wide-Field Radio Imaging Survey of the Southern Sky. I. Science goals, survey design and instrumentation
• Spectral Properties of Bright Fermi-detected Blazars in the Gamma-ray Band
• The radio/gamma-ray connection in Active Galactic Nuclei in the era of the Fermi Large Area Telescope
• A Statistical Approach to Recognizing Source Classes for Unassociated Sources in the First Fermi-LAT Catalog
• Classification and Ranking of Fermi LAT Gamma-ray Sources from the 3FGL Catalog using Machine Learning Techniques
• Application of the Gaussian mixture model in pulsar astronomy -- pulsar classification and candidates ranking for {\it Fermi} 2FGL catalog
• An adaptive-binning method for generating constant-uncertainty/constant-significance light curves with Fermi-LAT data
• Ground-based detectors in very-high-energy gamma-ray astronomy
• Fermi's Sibyl: Mining the gamma-ray sky for dark matter subhaloes
• The radio/gamma-ray connection in Fermi-blazars
• Characterizing the Optical Variability of Bright Blazars: Variability-Based Selection of Fermi AGN
• Optical Spectroscopic Observations of Gamma-ray Blazar Candidates. V. TNG, KPNO, and OAN Observations of Blazar Candidates of Uncertain Type in the Northern Hemisphere
• Gamma-Ray Active Galactic Nucleus Type through Machine-Learning Algorithms
• Search for gamma-ray-emitting active galactic nuclei in the Fermi-LAT unassociated sample using machine learning
• Flaring Patterns in Blazars
• Jets, black holes and disks in blazars

Cited by in corpus (39)

• Fermi Large Area Telescope Fourth Source Catalog
• The Fourth Catalog of Active Galactic Nuclei Detected by the Fermi Large Area Telescope
• MOJAVE XIX: Brightness Temperatures and Intrinsic Properties of Blazar Jets
• The Gamma-ray Blazar Quest: new optical spectra, state of art and future perspectives
• Research and characterisation of blazar candidates among the Fermi/LAT 3FGL catalogue using multivariate classifications
• 3FGLzoo. Classifying 3FGL Unassociated Fermi-LAT Gamma-ray Sources by Artificial Neural Networks
• Evaluating the optical classification of Fermi BCUs using machine learning
• Classification of New X-ray Counterparts for Fermi Unassociated Gamma Ray Sources Using the Swift X-Ray Telescope
• Classification of Blazar Candidates of Uncertain Type from the Fermi LAT 8-Year Source Catalog with an Artificial Neural Network
• Classification of Fermi-LAT sources with deep learning using energy and time spectra
• Evaluating the classification of Fermi BCUs from the 4FGL Catalog Using Machine Learning
• Searching for AGN and Pulsar Candidates in 4FGL Unassociated Sources Using Machine Learning
• Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge
• INTEGRAL view of AGN
• Optimizing neural network techniques in classifying Fermi-LAT gamma-ray sources
• Predicting the redshift of gamma-ray loud AGNs using supervised machine learning
• Predicting the redshift of gamma-ray loud AGNs using Supervised Machine Learning: Part 2
• Gradient boosting decision trees classification of blazars of uncertain type in the fourth Fermi-LAT catalog
• Artificial Neural Network Classification of 4FGL Sources
• Machine learning methods for constructing probabilistic Fermi-LAT catalogs
• Machine Learning applied to Multifrequency Data in Astrophysics: Blazar Classification
• Searching for TeV Candidates in 4LAC High-synchrotron-peaked Frequency BL Lac Objects
• Optical spectroscopic classification of a selection of Southern Hemisphere Fermi-LAT unclassified blazars
• Evaluating Optical Classification for {\em Fermi} Blazar Candidates with a Statistical method using Broadband Spectral Indices
• Classification of blazar candidates of unknown type in Fermi 4LAC by unanimous voting from multiple Machine Learning Algorithms
• A Combined Radio Multi-Survey Catalog of Fermi Unassociated Sources
• On the physical association of Fermi-LAT blazars with their low-energy counterparts
• Classification of the \emph{Fermi}-LAT Blazar Candidates of Uncertain type using eXtreme Gradient Boosting
• Search for AGN counterparts of unidentified Fermi-LAT sources with optical polarimetry: Demonstration of the technique
• Relativistic plasmas in AGN jets - From synchrotron radiation to $\gamma$-ray emission
• Fermi LAT AGN classification using supervised machine learning
• Identifying TeV Source Candidates among Fermi-LAT Unclassified Blazars
• A Hybrid method of accurate classification for Blazars Of Uncertain Type in Fermi LAT Catalogs
• A multiwavelength study of the flat spectrum radio-quasar NVSS J141922-083830 covering four flaring episodes
• Constraints on Physical Conditions for the Acceleration on Ultra-high-energy Cosmic Rays in Nearby Active Galactic Nuclei Observed with the Fermi Large Area Telescope
• An empirical "high-confidence" candidate zone for $Fermi$ BL Lacertae objects
• Assessing the capability of random forest to predict the evolution of enhanced gamma-ray states of active galactic nuclei
• Classification of Fermi-LAT blazars with Bayesian neural networks
• INTEGRAL View of TeV Sources: A Legacy for the CTA Project