Eur. Phys. J. C (2026) 86: 762
https://doi.org/10.1140/epjc/s10052-026-16010-6

Regular Article - Theoretical Physics

Revisiting the evidence for dynamical dark energy: from DES-SN5Y to DES-Dovekie

¹ Department of Physics, St. Xavier’s College, Tribhuvan University, Kathmandu, Nepal
² Kimyo International University in Tashkent, Shota Rustaveli str. 156, 100121, Tashkent, Uzbekistan
³ National University of Uzbekistan, 100174, Tashkent, Uzbekistan
⁴ Research Center of Astrophysics and Cosmology, Khazar University, 41 Mehseti Street, AZ1096, Baku, Azerbaijan
⁵ Department of Physics, Faculty of Science, Istanbul University, 34134, Istanbul, Turkey
⁶ School of Science and College of Graduate Studies, Walailak University, 80160, Nakhon Si Thammarat, Thailand
⁷ University of Tashkent for Applied Sciences, Str. Gavhar 1, 100149, Tashkent, Uzbekistan

^a This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 2 April 2026
Accepted: 16 June 2026
Published online: 3 July 2026

Abstract

Recent analyses combining DESI DR2 BAO measurements with CMB and supernova data have suggested a preference for dynamical dark energy, particularly when using the DES-SN5Y and DES-SN5Y $(z>0.1)$ supernova samples. With the revision of this dataset into the DES-Dovekie compilation, it is important to reassess the robustness of this result. In this work, we analyze a broad class of dark energy parametrizations, including wCDM, $w_0{w}_a$CDM, BA, JBP, Efstathiou, and GEDE models, using DESI DR2 BAO, a compressed CMB likelihood, and supernova data. We find that the DES-SN5Y dataset consistently yields a stronger preference for deviations from $\mathrm{\Lambda }$CDM compared to DES-Dovekie. In particular, redshift-dependent parametrizations favor the region $w_0>-1$ and $w_a<0$, corresponding to a Quintom-B–type evolution with phantom crossing. This behavior is observed across multiple models, indicating that it is not specific to a single parametrization. We find that the DES-SN5Y $(z>0.1)$ sample also preserves the same qualitative behavior, although the deviations from the $\mathrm{\Lambda }$CDM limit become significantly weaker compared to the full DES-SN5Y sample. However, when DES-Dovekie is used, the statistical preference for dynamical dark energy is significantly reduced. The improvement over $\mathrm{\Lambda }$CDM drops to below the $1\sigma$ level for most models, and the Bayesian evidence weakens from moderate to weak or inconclusive. Similarly, for the DES-SN5Y $(z>0.1)$ sample, the preference for dynamical dark energy becomes intermediate between the DES-SN5Y and DES-Dovekie cases, with mostly weak or inconclusive evidence. Overall, the DES-Dovekie and DES-SN5Y $(z>0.1)$ datasets weaken the preference for dynamical dark energy compared to the full DES-SN5Y dataset.