Constraints on the baryon density from fast radio bursts using a non-parametric reconstruction of the Hubble parameter

Abstract

In this study, we use a sample of 130 well-localized fast radio bursts (FRBs) to constrain the physical baryon density bh2, 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 H(z) obtained from cosmic chronometer data using the ReFANN neural-network framework, independently of the FRB sample. Within a Bayesian analysis, we jointly infer bh2 and the parameters of a log-normal host-galaxy distribution, namely its median eμ and logarithmic scatter σ host, using both real FRB data and a mock catalog. For the real sample, we obtain bh2=0.022360.00090, eμ=178.15+16.51-16.97~pc\,cm-3, and σ host=0.794+0.064-0.067. For the mock catalog, we find bh2=0.022480.00018, eμ=182.36+6.83-6.48~pc\,cm-3, and σ host=0.711+0.024-0.025. The baryon density constraint from the real FRB sample is in excellent agreement with both Big Bang Nucleosynthesis and Planck CMB determinations, differing from their central values by only 0.05\%. The mock analysis further illustrates the potential of future FRB samples, reducing the uncertainty on bh2 to the sub-percent level while remaining statistically consistent with early-Universe constraints. Our findings show that combining FRB dispersion measures with a non-parametric reconstruction of the expansion history provides a robust pathway to constrain both cosmological and astrophysical parameters, establishing FRBs as a complementary low-redshift probe of the baryon density.

0

Turn this paper into a full lesson

ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.

Discussion (0)

Sign in to join the discussion.

Loading comments…