CosmoDS: A Python toolkit for constraining cosmological models via dynamical systems analysis with Cobaya

TL;DR

CosmoDS is a Python toolkit integrated with Cobaya that enables researchers to analyze and constrain cosmological models at the background level using dynamical systems methods, facilitating stability and evolution studies.

Contribution

It introduces a new toolkit that combines dynamical systems analysis with Cobaya's inference capabilities for cosmological model constraints.

Findings

Provides a flexible framework for background cosmology analysis.

Enables stability analysis of dark energy models.

Integrates with Cobaya for parameter estimation.

Abstract

We present a toolkit, CosmoDS, designed to study cosmological models at the background level using dynamical system analysis within the Cobaya framework. Dynamical system analysis is a powerful mathematical approach for studying nonlinear systems and is widely used in cosmology to investigate the stability and evolution of different cosmological models, particularly those involving dark energy. In this code, we provide a framework for constraining cosmological models using a dynamical system formulation. Most importantly, the toolkit is directly integrated with the Cobaya interface, allowing users to take advantage of the sophisticated statistical and inference tools already implemented in Cobaya for cosmological parameter estimation and model analysis.