New tests of cosmic distance duality relation with DESI 2024 BAO observations
Qiumin Wang, Shuo Cao, Jianyong Jiang, Kaituo Zhang, Xinyue Jiang, Tonghua Liu, Chengsheng Mu, and Dadian Cheng

TL;DR
This paper tests the cosmic distance duality relation using recent BAO data from DESI, BOSS/eBOSS, and DES, employing a novel, model-independent method with neural network reconstruction, finding no deviation at low redshift but evidence of deviation at high redshift.
Contribution
It introduces a new, model-independent, neural network-based method to test the CDDR using BAO and SN Ia data, eliminating nuisance parameters and providing high-redshift deviation evidence.
Findings
No significant deviation from CDDR at low redshift
Evidence of deviation at high redshifts ($z=2.33$ and $z=2.334$)
Demonstrates BAO as a powerful tool for fundamental cosmological tests
Abstract
In this paper, we test the cosmic distance duality relation (CDDR), as required by the Etherington reciprocity theorem, which connects the angular diameter distance and the luminosity distance via the relation \( D_{\rm L}(z) = D_{\rm A}(z)(1+z)^2 \). Our analysis is based on the latest baryon acoustic oscillation (BAO) measurements provided by the Dark Energy Survey (DES), the Baryon Oscillation Spectroscopic Survey (BOSS)/Extended BOSS (eBOSS), and the Dark Energy Spectroscopic Instrument (DESI) surveys. Specifically, an unbiased test of the CDDR is performed through a novel, model-independent method inspired by the two-point diagnostic approach, with DES-SN5YR and Pantheon type Ia supernova (SN Ia) sample reconstructed using the Artificial Neural Network (ANN) technique. This methodology effectively eliminates all nuisance parameters, including the sound horizon scale \( r_{\rm d} \)…
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Taxonomy
TopicsCalibration and Measurement Techniques
