Kinematic state of an interacting cosmology modeled with Chebyshev polynomials
Freddy Cueva Solano

TL;DR
This paper reconstructs the interaction between dark matter and dark energy using Chebyshev polynomials, analyzing their effects on cosmographic parameters to understand the universe's kinematic state and distinguish different dark energy models.
Contribution
It introduces a novel Chebyshev polynomial-based reconstruction of the interaction term and dark energy EoS, constrained by geometric data, to study their impact on cosmography.
Findings
Cosmographic parameters deviate significantly from standard model predictions.
Different dark energy scenarios can be distinguished using high-order cosmographic parameters.
Model parameters are constrained using MCMC with combined geometric data.
Abstract
In a spatially flat universe and for an interacting cosmology, we have reconstructed the interaction term, , between a cold dark matter (DM) fluid and a dark energy (DE) fluid, as well as a time-varying equation of state (EoS) parameter , and have explored their cosmological impacts on the amplitudes of the first six cosmographic parameters, which allow us to extract information about the kinematic state of the universe today. Here, both and have been modeled in terms of the Chebyshev polynomials. Then, via a Markov-Chain Monte Carlo (MCMC) method, we have constrained the model parameter space by using a combined analysis of geometric data. Our results show that the evolution curves of the cosmographic parameters deviate strongly from those predicted in the standard model when are compared, namely, they are much more sensitive to …
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCosmology and Gravitation Theories · Galaxies: Formation, Evolution, Phenomena · Complex Systems and Time Series Analysis
