4FGL J0621.2-4648 , the SIMBAD biblio

4FGL J0621.2-4648 , the SIMBAD biblio (12 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.16CEST00:26:18


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Title First 3 Authors
2021ApJS..253...46P viz 17       D               1 1078 38 The central engines of Fermi blazars. PALIYA V.S., DOMINGUEZ A., AJELLO M., et al.
2021MNRAS.505.5853G 17       D               1 5834 ~ Artificial Neural Network classification of 4FGL sources. GERMANI S., TOSTI G., LUBRANO P., et al.
2022ApJ...925...40X viz 17       D               1 668 12 The Relativistic Jet and Central Engine of Fermi Blazars. XIAO H., OUYANG Z., ZHANG L., et al.
2022A&A...660A..87B viz 17       D               1 6191 10 Machine learning methods for constructing probabilistic Fermi-LAT catalogs. BHAT A. and MALYSHEV D.
2022ApJS..260...53A viz 17       D               1 6710 133 Incremental Fermi Large Area Telescope Fourth Source Catalog. ABDOLLAHI S., ACERO F., BALDINI L., et al.
2022PASP..134h4102H viz 17       D               1 620 ~ Constraining the γ-Ray Emission Region for Fermi-detected FSRQs by the Seed Photon Approach. HUANG D., LI Z., LIAO J., et al.
2022ApJ...936..146X viz 17       D               2 661 2 An Extensive Study of Blazar Broad Emission Line: Changing-look Blazars and the Baldwin Effect. XIAO H., FAN J., OUYANG Z., et al.
2022ApJS..262...18Y viz 17       D               1 2709 8 The Spectral Energy Distributions for 4FGL Blazars. YANG J.H., FAN J.H., LIU Y., et al.
2022ApJS..263...24A viz 17       D               1 3828 15 The Fourth Catalog of Active Galactic Nuclei Detected by the Fermi Large Area Telescope: Data Release 3. AJELLO M., BALDINI L., BALLET J., et al.
2023ApJS..268...23F viz 17       D               1 2708 ~ Characterizing the Emission Region Properties of Blazars. FAN J., XIAO H., YANG W., et al.
2024MNRAS.530.2282D 1940 ~ Predicting conditional probability distributions of redshifts of Active Galactic Nuclei using Hierarchical Correlation Reconstruction. DUDA J. and BHATTA G.
2025PASP..137f4105D 19       D               1 290 ~ Improved Fermi Blazar Candidate Classifications with SRG/eROSITA X-Ray Counterparts Using Machine Learning. DING J. and RODRIGUEZ A.C.

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