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January 24, 2026Monthly Notices of the Royal Astronomical Society16 citationsOpen Access

A Novel Pipeline for the Identification of New Gamma-Ray Blazars from the 4FGL-Xiang Catalog Based on Multi-wavelength Flux Distributions

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XCXiufa ChenYYYingzhi YePFPeng Feng

Key Points

  • This research aims to create a robust method for identifying new gamma-ray blazars using multi-wavelength data.
  • Constructed high-precision catalogs: 4FGL-Xiang-DR2 and 5BZCAT_err.
  • Developed a four-step analytical pipeline for cross-matching and flux distribution analysis.
  • Applied statistical metrics, particularly kurtosis, for classification of blazars.
  • Identified 17 new blazars using multi-band flux data.
  • Kurtosis successfully discriminates between blazar types with a threshold of MAD > 1.64.
  • Significant divergence in flux distributions was observed across multiple bands with JSD > 0.3.
  • The proposed Box-Cox+TND model fits the flux distributions effectively.
  • Out of 17 identified candidates, 15 are consistent with known blazar properties within the 2σ confidence interval.

Abstract

Abstract The identification and classification of Fermi blazars are core topics in high-energy astrophysics. To enable precise spatial cross-identification, we constructed two high-precision catalogs: the updated 4FGL-Xiang-DR2 (DR2) and a supplementary version of the fifth edition of Roma-BZCAT (5BZCATₑrr). We then developed and applied a novel four-step analytical pipeline combining cross-matching with the statistical analysis of multi-band flux distributions to identify new Fermi blazars. The analytical pipeline has yielded several key results in the systematic comparison of BZBs and BZQs. We found that among single statistical metrics, kurtosis is the most powerful discriminator (MAD 1. 64). At the overall distribution level, the 1. 4 GHz, 843 MHz, 5 GHz, 0. 1–2. 4 keV, and 0. 3–10 keV bands show significant divergence (JSD 0. 3). Building on these findings, our proposed “Box-Cox+TND” model successfully fits the observed flux distributions between BZBs and BZQs. Applying this entire pipeline, we successfully identified 17 new blazars. The validity of these associations is strongly supported by our multi-wavelength flux model, which confirms that 15 of the 17 candidates are statistically consistent with the known blazar population, falling within the 2σ confidence interval. Although the two remaining sources exhibit some statistical deviation in the gamma-ray band, their strong consistency in other wavebands, coupled with high spatial association probabilities, leads us to conclude that their associations are also reliable and should not be readily excluded.

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Cite This Study

Chen et al. (2026) studied this question.

synapsesocial.com/papers/6974610cbb9d90c67120aefbhttps://doi.org/10.1093/mnras/stag150
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