Constraining the Hubble constant and its lower limit from the proper motion of extragalactic radio jets

TL;DR

This paper introduces a model-free, distance-free method to constrain the lower limit of the Hubble constant using proper motions of extragalactic radio jets, addressing the current measurement discrepancy.

Contribution

It proposes a novel approach combining cosmology and geometrical relations to estimate $H_0$ without relying on cosmological models or distances.

Findings

Increasing sample size improves constraints on $H_0$ and jet velocity distribution.

Higher measurement accuracy enhances the precision of $H_0$ constraints.

The method can differentiate cosmologies using K-S tests on simulated data.

Abstract

The Hubble constant ($H_{0}$) is a measurement to describe the expansion rate of the Universe in the current era. However, there is a $4.4\sigma$ discrepancy between the measurements from the early Universe and the late Universe. In this research, we propose a model-free and distance-free method to constrain $H_{0}$. Combining Friedman-Lema\^itre-Robertson-Walker cosmology with geometrical relation of the proper motion of extragalactic jets, the lower limit ($H_{\rm 0,min}$) of $H_{0}$ can be determined using only three cosmology-free observables: the redshifts of the host galaxies, as well as the approaching and receding angular velocities of radio jets. Using these, we propose to use the Kolmogorov-Smirnov test (K-S test) between cumulative distribution functions of $H_{\rm 0,min}$ to differentiate cosmology. We simulate 100, 200, and 500 extragalactic jets with 3 levels of accuracy of the proper motion ($\mu_{a}$ and $\mu_{r}$), at $10\%$, $5\%$, and $1\%$, corresponding to the accuracies of the current and future radio interferometers. We perform K-S tests between the simulated samples as theoretical distributions with different $H_{0}$ and power-law index of velocity distribution of jets and mock observational data. Our result suggests increasing sample sizes leads to tighter constraints on both power-law index and the Hubble constant at moderate accuracy (i.e., $10\%$ and $5\%$) while at $1\%$ accuracy, increasing sample sizes leads to tighter constraints on power-law index more. Improving accuracy results in better constraints in the Hubble constant compared with the power-law index in all cases but it alleviates the degeneracy.