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

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 (5BZCAT_err). 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 “$\mathrm{Box\textrm{-}Cox+TND}$” 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.