Testing the cosmic distance-duality relation with localized fast radio bursts: a cosmological model-independent study

Abstract

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 $D_{\mathrm{A}}^{\mathrm{FRB}}(z)$ without assuming a parametric form for the expansion history. Possible deviations from CDDR are parameterized through three one-parameter models of $\hat{I}\cdot (z)\equiv D_{\mathrm{L}}/[(1+z{)}^2{D}_{\mathrm{A}}]$. 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 ${\mathrm{DM}}_{\mathrm{host}}=128.8\pm 34.1\mathrm{pc}\mathrm{c}{\mathrm{m}}^{-3}$ ($3\ddot{I}ƒ$ 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.