Dynamical dark energy in the light of DESI 2024 data
1
Issued Date
2025-05-01
Resource Type
ISSN
22126864
Scopus ID
2-s2.0-105001698653
Journal Title
Physics of the Dark Universe
Volume
48
Rights Holder(s)
SCOPUS
Bibliographic Citation
Physics of the Dark Universe Vol.48 (2025)
Suggested Citation
Roy N. Dynamical dark energy in the light of DESI 2024 data. Physics of the Dark Universe Vol.48 (2025). doi:10.1016/j.dark.2025.101912 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/109475
Title
Dynamical dark energy in the light of DESI 2024 data
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Author's Affiliation
Corresponding Author(s)
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Abstract
The latest findings from the DESI (Dark Energy Spectroscopic Instrument) data release 1 (DR1) Adame et al. (2024), combined with data from the cosmic microwave background and supernovae, suggest a preference for dynamical dark energy over the cosmological constant. This study has considered the Chevallier–Polarski–Linder (CPL) parameterization for the dark energy equation of state (EoS) and has indicated a possible phantom barrier crossing in the recent past. Despite CPL being the most commonly used parameterization, recent research has pointed out issues with its prior selection and parameter degeneracies. In this paper, we propose an alternative two-parameter parameterization of the dark energy equation of state (EoS). At higher redshifts, it behaves like the cosmological constant. At redshifts z<1, this parameterization closely approximates the CPL form but deviates from it at lower redshifts. Our findings also indicate that the current value of the EoS of dark energy resembles quintessence, with evidence of a recent crossing of the phantom barrier, supporting the conclusions in Adame et al. (2024). Furthermore, our model significantly reduces the Hubble tension to about 2.8σ when compared to Hubble Space Telescope and SH0ES data Riess et al. (2022), and to 1.6σ with standardized TRGB and Type Ia supernova data Scolnic et al. (2023). Bayesian model selection using Bayes factors and Akaike Information Criteria (ACI), shows a strong preference for our parameterization over the Λ CDM model, aligned with the DESI2024 results and favoring dynamical dark energy.
