Degeneracy and Discreteness in Cosmological Model Fitting

TL;DR

This paper investigates the degeneracy and discreteness issues in the DM cosmological model using observational data, introducing a new factor G to improve model differentiation and parameter constraint analysis.

Contribution

The paper introduces the factor G as a novel tool to quantify the influence of individual data points and enhance model discrimination in cosmological data fitting.

Findings

Higher |G| values improve model distinction.

G effectively constrains model parameters.

G enhances confidence in model selection.

Abstract

We explore the degeneracy and discreteness problems in the standard cosmological model (\Lambda CDM). We use the Observational Hubble Data (OHD) and the type Ia supernova (SNe Ia) data to study this issue. In order to describe the discreteness in fitting of data, we define a factor G to test the influence from each single data point and analyze the goodness of G. Our results indicate that a higher absolute value of G shows a better capability of distinguishing models, which means the parameters are restricted into smaller confidence intervals with a larger figure of merit evaluation. Consequently, we claim that the factor G is an effective way in model differentiation when using different models to fit the observational data.