Current Observational Constraints to Holographic Dark Energy Model with New Infrared cut-off via Markov Chain Monte Carlo Method
Yuting Wang, Lixin Xu

TL;DR
This study constrains the holographic dark energy model with a new IR cut-off using current cosmological data and MCMC, finding parameters consistent with observations but not favoring it over the standard Lambda-CDM model.
Contribution
First comprehensive observational constraints on the holographic dark energy model with a new IR cut-off using MCMC and multiple datasets.
Findings
Best-fit parameters for flat and non-flat models obtained.
Dark energy equation of state close to -1, indicating phantom-like behavior.
Current data do not favor holographic dark energy over Lambda-CDM.
Abstract
In this paper, the holographic dark energy model with new infrared (IR) cut-off for both the flat case and the non-flat case are confronted with the combined constraints of current cosmological observations: type Ia Supernovae, Baryon Acoustic Oscillations, current Cosmic Microwave Background, and the observational hubble data. By utilizing the Markov Chain Monte Carlo (MCMC) method, we obtain the best fit values of the parameters with errors in the flat model: , , , , , . In the non-flat model, the constraint results are found in regions:…
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