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

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Abstract In a recent paper 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 ∼ 1 σ .
Title: Calibration-independent consistency test of BAO and SNIa data: update
Description:
Abstract In a recent paper 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 ∼ 1 σ .

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