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Constraining the curvature density parameter in cosmology

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abstract

The cosmic curvature density parameter has been constrained in the present work independent of any background cosmological model. The reconstruction is performed adopting the non-parametric Gaussian Processes (GP). The constraints on $\Omega_{k0}$ are obtained via a Markov Chain Monte Carlo (MCMC) analysis. Late-time cosmological probes viz., the Supernova (SN) distance modulus data, the Cosmic Chronometer (CC) and the radial Baryon Acoustic Oscillations ($r$BAO) measurements of the Hubble data have been utilized for this purpose. The results are further combined with the data from redshift space distortions (RSD) which studies the growth of large scale structure in the universe. The only \textit{a priori} assumption is that the universe is homogeneous and isotropic, described by the FLRW metric. Results indicate that a spatially flat universe is well consistent in 2$\sigma$ within the domain of reconstruction $0<z<2$ for the background data. On combining the RSD data we find that the results obtained are consistent with spatial flatness mostly within 2$\sigma$ and always within 3$\sigma$ in the domain of reconstruction $0<z<2$.

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astro-ph.CO 1

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2024 1

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representative citing papers

Non-parametric reconstructions of cosmic curvature: current constraints and forecasts

astro-ph.CO · 2024-11-28 · conditional · novelty 4.0

Using Gaussian-process reconstructions of cosmic distances and expansion rates, the authors find no statistically significant departure from flatness or from the cosmological principle in current data, and they forecast much tighter constraints from upcoming J-PAS and LIGO observations.

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  • Non-parametric reconstructions of cosmic curvature: current constraints and forecasts astro-ph.CO · 2024-11-28 · conditional · none · ref 30 · internal anchor

    Using Gaussian-process reconstructions of cosmic distances and expansion rates, the authors find no statistically significant departure from flatness or from the cosmological principle in current data, and they forecast much tighter constraints from upcoming J-PAS and LIGO observations.