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

Bikash R. Dinda, Roy Maartens, Chris Clarkson

TL;DR

This work presents a calibration-independent test of consistency between uncalibrated BAO and SNIa distances by leveraging the Alcock–Paczynski ratio $F_{ m AP}$ and Gaussian Process reconstructions. By comparing DESI DR2 BAO data with SNIa distance moduli from Union3, Pantheon+, and the updated DES-Dovekie dataset, the study quantifies the level of tension via $\sigma_{ m tension}(z)$ and finds, overall, consistency at the $\sim 1\sigma$ level across redshift. The updated DES-Dovekie data largely remove the prior tension seen with DES-Y5, supporting a model-independent concordance between these distance tracers. The results bolster the robustness of cross-dataset consistency checks and demonstrate the utility of GP methods in calibrating cosmological inferences without assuming a specific dark energy or gravity model.

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 $\sim 1σ$.

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

TL;DR

This work presents a calibration-independent test of consistency between uncalibrated BAO and SNIa distances by leveraging the Alcock–Paczynski ratio and Gaussian Process reconstructions. By comparing DESI DR2 BAO data with SNIa distance moduli from Union3, Pantheon+, and the updated DES-Dovekie dataset, the study quantifies the level of tension via and finds, overall, consistency at the level across redshift. The updated DES-Dovekie data largely remove the prior tension seen with DES-Y5, supporting a model-independent concordance between these distance tracers. The results bolster the robustness of cross-dataset consistency checks and demonstrate the utility of GP methods in calibrating cosmological inferences without assuming a specific dark energy or gravity model.

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 .
Paper Structure (3 sections, 4 equations, 1 figure)

This paper contains 3 sections, 4 equations, 1 figure.

Table of Contents

  1. Introduction
  2. Consistency test of uncalibrated BAO and SNIa distances
  3. Conclusions

Figures (1)

  • Figure 1: Left:$F_{\rm AP}$ comparison of SNIa data to DESI data. Right: Tension between SNIa and DESI datasets, as given by \ref{['eq:tension']}.