Determination of cosmic curvature independent of the sound horizon and $H_0$ using BOSS/eBOSS and DESI DR1 BAO observations

TL;DR

This paper introduces a model-independent approach to measure cosmic curvature using BAO data from BOSS/eBOSS and DESI DR1, avoiding dependence on the sound horizon and Hubble constant, and compares reconstruction methods.

Contribution

It develops a novel method that circumvents sound horizon and H0 influence, applying Gaussian process and neural network techniques to BAO data for curvature estimation.

Findings

Cosmic curvature constrained to Ω_K ≈ -0.04 with GP method.

Results consistent with a flat universe within uncertainties.

Comparable precision between BOSS/eBOSS and DESI DR1 data samples.

Abstract

We present an improved model-independent method for determining the cosmic curvature using the observations of Baryon Acoustic Oscillations (BAOs) and the Hubble parameter. The purpose of this work is to provide insights into late-universe curvature measurements using available observational data and techniques. Thus, we use two sources of BAO data sets, BOSS/eBOSS and latest DESI DR1, and two reconstruction methods, Gaussian process (GP) and artificial neural network (ANN). It is important to highlight that our method circumvents influence induced by the sound horizon in BAO observations and the Hubble constant. Combining BAO data from BOSS/eBOSS plus DESI DR1, we find that the constraint on the cosmic curvature results in $\Omega_K=-0.040^{+0.142}_{-0.145}$ with an observational uncertainty of $1\sigma$ in the framework of GP method. This result changes to $\Omega_K=-0.010^{+0.405}_{-0.424}$ when the ANN method is applied. Further comparative analysis of samples from two BAO data sources, we find that there is almost no difference between the two samples. Although the curvature values obtained from the data samples using DESI DR1 are on the slightly positive and the samples using BOSS/eBOSS are on the slightly negative, these results both report that our universe has a flat spatial curvature within uncertainties, and the precision of constraining the curvature with two BAO samples is almost equal.