Constraints on the baryon density from fast radio bursts using a non-parametric reconstruction of the Hubble parameter
L\'azaro L. Sales, Klecio E. L. de Farias, Amilcar R. Queiroz, Rafael A. Batista, Bruno W. Ribeiro, Raiff H. Santos

TL;DR
This paper uses 130 localized fast radio bursts and a neural-network reconstructed Hubble parameter to precisely measure the baryon density, aligning with early-Universe estimates and demonstrating future potential.
Contribution
It introduces a non-parametric method combining FRB data and neural-network H(z) reconstruction to constrain baryon density and host galaxy properties.
Findings
Measured baryon density consistent with Big Bang Nucleosynthesis and Planck CMB.
Mock data suggests future FRB samples can reduce uncertainty to sub-percent levels.
Method provides a robust low-redshift probe of baryon density.
Abstract
In this study, we use a sample of 130 well-localized fast radio bursts (FRBs) to constrain the physical baryon density , and the astrophysical contribution from host galaxies. The cosmological dependence entering the intergalactic dispersion measure is described through a non-parametric reconstruction of the Hubble parameter obtained from cosmic chronometer data using the \texttt{ReFANN} neural-network framework, independently of the FRB sample. Within a Bayesian analysis, we jointly infer and the parameters of a log-normal host-galaxy distribution, namely its median and logarithmic scatter , using both real FRB data and a mock catalog. For the real sample, we obtain , , and $\sigma_{\rm…
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