Calibration-independent consistency test of BAO and SNIa data: update

TL;DR

This paper introduces a calibration-independent method using Gaussian Processes to test the consistency of BAO and SNIa datasets, confirming their agreement within 1 sigma after recent updates.

Contribution

It presents an updated, model-independent consistency test for BAO and SNIa data that does not rely on calibration parameters or specific cosmological models.

Findings

DES-Y5 SNIa data initially showed tension, but the updated DES-Dovekie data resolves this.

All datasets from DESI DR2 BAO, Union3, Pantheon+, and DES-Dovekie are consistent within approximately 1 sigma.

The method effectively assesses dataset compatibility without assumptions on dark energy or sound horizon.

Abstract

In a recent paper, arXiv:2509.19899, we presented a new method to test the consistency between uncalibrated BAO and SNIa data through a common parameter, the Alcock-Paczynski variable. Using Gaussian Processes, we can determine if various datasets are consistent, independently of dark energy or modified gravity models, and of the sound horizon and SNIa peak magnitude. We found that the DES-Y5 SNIa data showed non-negligible tension with other datasets. However, the recent update DES-Dovekie removes this tension. We find that all uncalibrated data from DESI DR2 BAO and three SNIa datasets, Union3, Pantheon+, and DES-Dovekie, are consistent with each other within $\sim 1\sigma$.