Analytical gaussian process cosmography: unveiling insights into matter-energy density parameter at present

dc.contributor.authorDinda, Bikash Ranjan
dc.date.accessioned2025-01-22T06:46:55Z
dc.date.available2025-01-22T06:46:55Z
dc.date.issued2024
dc.description.abstractIn this study, we introduce a novel analytical Gaussian Process (GP) cosmography methodology, leveraging the differentiable properties of GPs to derive key cosmological quantities analytically. Our approach combines cosmic chronometer (CC) Hubble parameter data with growth rate (f) observations to constrain the Ωm0 parameter, offering insights into the underlying dynamics of the Universe. By formulating a consistency relation independent of specific cosmological models, we analyze under a flat FLRW metric and first-order Newtonian perturbation theory framework. Our analytical approach simplifies the process of Gaussian Process regression (GPR), providing a more efficient means of handling large datasets while offering deeper interpretability of results. We demonstrate the effectiveness of our methodology by deriving precise constraints on Ωm0h2, revealing Ωm0h2=0.139±0.017. Moreover, leveraging H0 observations, we further constrain Ωm0, uncovering an inverse correlation between mean H0 and Ωm0. Our investigation offers a proof of concept for analytical GP cosmography, highlighting the advantages of analytical methods in cosmological parameter estimation.
dc.identifier.citationDinda, B.R., 2024. Analytical Gaussian process cosmography: unveiling insights into matter-energy density parameter at present. The European Physical Journal C, 84(4), pp.1-12.
dc.identifier.urihttps://doi.org/10.1140/epjc/s10052-024-12774-x
dc.identifier.urihttps://hdl.handle.net/10566/19891
dc.language.isoen
dc.publisherSpringer Nature
dc.subjectChronometers
dc.subjectCosmology
dc.subjectGaussian distribution
dc.subjectCosmological modeling
dc.subjectLarge datasets
dc.titleAnalytical gaussian process cosmography: unveiling insights into matter-energy density parameter at present
dc.typeArticle

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