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Cosmological constraints on dark energy models using DESI BAO 2024

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arxiv 2412.04830 v1 pith:6Y4TWTTC submitted 2024-12-06 astro-ph.CO

Cosmological constraints on dark energy models using DESI BAO 2024

classification astro-ph.CO
keywords datadeviationdarkdesienergylambdamodelpoints
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Recently, the measurements of baryon acoustic oscillations (BAO) by the Dark Energy Spectroscopic Instrument (DESI) indicate a potential deviation from the standard $\Lambda$CDM model. Some studies suggest that the data points from the luminous red galaxies (LRG) survey in DESI BAO data may contribute to this discrepancy. In this work, our main goal is to investigate whether this deviation is caused by the parameterization of the equation of state (EoS) of dark energy (DE). Hence, we have examined four popular parameterized dark energy models in our analysis: the Chevallier-Polarski-Linder (CPL), Barboza-Alcaniz (BA), Jassal-Bagla-Padmanabhan (JBP), and Feng-Shen-Li-Li (FSLL) parameterizations. Considering that LRG1 and LRG2 data points may lead to deviation from the $\Lambda$CDM model, we use two versions of DESI BAO data, differing in whether these data points are included. Additionally, to break the parameter degeneracies and obtain robust constraint results, we introduce Type Ia supernovae (SNe Ia) and quasars (QSO) in our analysis. Our findings indicate that in these parameterizations, the deviation from ($w_0$,$w_{1}$)=(-1,0) becomes more pronounced when using the combined data from DESI BAO, SNe Ia, and QSO compilations. Here, $w_{0}$ and $w_{1}$ represent the EoS of DE. It suggests that the parameterizations of the EoS of DE have little impact on the deviation from the $\Lambda$CDM model. Besides, our analysis potentially hints that dark energy may have dynamic properties. In addition, the results obtained from different BAO datasets demonstrate that the LRG1 and LRG2 data points do indeed contribute to a deviation from the $\Lambda$CDM model. Finally, according to the statistical criteria, the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), the joint constraints provide substantial observational support to the BA and FSLL models.

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Cited by 6 Pith papers

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