JOURNAL ARTICLE
Observational constraints on freezing quintessence in a nonlinear f(R,Lm) gravity.
Published In: International Journal of Geometric Methods in Modern Physics, 2025, v. 22, n. 12. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Myrzakulov, Yerlan; Koussour, M.; Çalíşkan, A.; Güdekli, E.; Muminov, S.; Rayimbaev, J. 3 of 3
Abstract
In this paper, we investigate the freezing quintessence scenario in late-time cosmic expansion using a nonlinear f (R , L m) gravity model, f (R , L m) = R 2 + L m α , where α is a free parameter. We consider a solution for this model using an appropriate parametrization of the scale factor, and then the model is constrained by observational datasets, including CC, Pantheon + (SN), and CC + SN + BAO. Our analysis yields results aligning closely with observational data. The Hubble parameter, deceleration parameter, matter-energy density, and EoS parameter of our model exhibit expected trends over cosmic time, supporting its physical validity. Furthermore, the model demonstrates consistency with the Λ CDM model in late times, displaying freezing behavior in the ω − ω ′ plane and stability against density perturbations. Our findings suggest that the modified f (R , L m) gravity model is a credible approach to describing the universe's accelerating phase. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Geometric Methods in Modern Physics. 2025/10, Vol. 22, Issue 12, p1
- Document Type:Article
- Subject Area:History
- Publication Date:2025
- ISSN:0219-8878
- DOI:10.1142/S0219887825500926
- Accession Number:188498818
- Copyright Statement:Copyright of International Journal of Geometric Methods in Modern Physics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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