Code Repository for 'Constraints on AvERA Cosmologies from Cosmic Chronometers and Type Ia Supernovae'

This repository is for the paper 'Constraints on AvERA Cosmologies from Cosmic Chronometers and Type Ia Supernovae' by Adrienn Pataki et al..

The repository contains Python code for fitting the AvERA model and the flat ΛCDM model to the Cosmic Chronometer (CC) and Type Ia Supernova (SNIa) datasets, using the dynesty package for dynamic nested sampling. Detailed descriptions and usage instructions are included within the code files.

Required input files:

• AvERA simulation output files: HSTART1191_100Mpc_Granul_s08159_IC_LCDM_Logfile.dat (available in this repository). The output format for the Logfile: t[Gy] error h[Gy] a z H[km/s/Mpc] q Omega_m_eff;
• CC measurement and covariance matrix data: Hz_data_MM22_33datapoints.dat and data_MM20.dat (available in this repository);
• SN data and covariance matrix are available: PantheonPlusSH0ES/DataRelease.

The repository also includes PDF files that present the fitting results as corner plots, illustrating the posterior distributions of the fitted parameters. These plots display the projections of the dynesty samples in one- and two-dimensional parameter spaces. The 1D histograms show the median of the posterior parameter distributions, along with the 1σ uncertainties represented by the 16th and 84th percentiles. In the 2D distribution panels, contours are plotted at 0.5σ, 1σ, 1.5σ, and 2σ levels.

Corresponding author: Adrienn Pataki, patakia@student.elte.hu