A Reliable Calibration of HII Galaxies Hubble Diagram with Cosmic Chronometers and Artificial Neural Network

TL;DR

This paper improves the calibration of HII galaxies as standard candles for measuring the Hubble constant by using cosmic chronometers and neural networks, leading to a reliable, model-independent estimate of H_0 consistent with Planck results.

Contribution

It introduces a non-parametric neural network approach to calibrate HII galaxy data with cosmic chronometers, removing assumptions about cosmic flatness and enhancing calibration reliability.

Findings

Calibrated HII galaxy Hubble diagram yields H_0=65.9 km/s/Mpc.

Method removes dependence on cosmic flatness assumptions.

Results are consistent with Planck 2018 measurements.

Abstract

The $L-\sigma$ relation of HII galaxies (HIIGx) calibrated by a distance indicator is a reliable standard candle for measuring the Hubble constant $H_0$. The most straightforward calibration technique anchors them with the first tier of distance ladders from the same galaxies. Recently another promising method that uses the cosmological model-independent Cosmic Chronometers (CC) as a calibrator has been proposed. We promote this technique by removing the assumptions about the cosmic flatness and using a non-parametric Artificial Neural Network for the data reconstruction process. We observe a correlation between the cosmic curvature density parameter and the slope of the $L-\sigma$ relation, thereby improving the reliability of the calibration. Using the calibrated HIIGx Hubble diagram, we obtain a Type Ia Supernovae Hubble diagram free of the conventional assumption about $H_0$. Finally we get a value of $H_0=65.9_{-2.9}^{+3.0} \mathrm{km s^{-1} Mpc^{-1}}$, which is compatible with latest Planck18 measurement.