We test the Etherington cosmic distance-duality relation (CDDR), by comparing Type Ia supernova (SNIa) luminosity-distance information from the Pantheon+ compilation with an angular-diameter-distance reconstructed from localized Fast Radio Bursts (FRBs). The core of our methodology is a data-driven reconstruction from FRBs using artificial neural networks (ANNs): we infer a smooth mean extragalactic dispersion-measure relation and use its redshift derivative to recover H(z) and hence DAFRB(z) without assuming a parametric form for the expansion history. Possible deviations from CDDR are parameterized through three one-parameter models of η(z)≡DL/[(1+z)2DA]. We implement two complementary likelihoods: (i) a direct approach using individual SNIa with the full Pantheon+ covariance, and (ii) a machine-learning approach in which we reconstruct the SN Hubble diagram on the FRB redshift grid, propagating SN and FRB uncertainties into non-diagonal covariance matrices via Monte Carlo and bootstrap realizations. Within the FRB reconstruction, we anchor the mean extragalactic dispersion measure at z=0, which yields a data-driven constraint on the average host/near-source contribution DMhost=128.8±34.1pccm−3 (3σ of statistical confidence). We find that both likelihood implementations give consistent posteriors and no statistically significant evidence for departures from CDDR at the current precision.
@article{arxiv.2602.16869,
title = {Testing the cosmic distance-duality relation with localized fast radio bursts: a cosmological model-independent study},
author = {Jéferson A. S. Fortunato and Surajit Kalita and Amanda Weltman},
journal= {arXiv preprint arXiv:2602.16869},
year = {2026}
}