$\Lambda$CDM model against redshift-binned data: A mock analysis based on SNIa and Cosmic Chronometers
Saeed Pourojaghi, Mohammad Malekjani

TL;DR
This study uses mock data from SNIa and cosmic chronometers to investigate potential redshift dependence of $ m extLambda$CDM parameters, revealing possible deviations at different redshifts that could suggest new physics beyond the standard model.
Contribution
It introduces a novel method of analyzing redshift-dependent parameters in $ m extLambda$CDM using mock data and binning techniques, highlighting potential deviations at high and low redshifts.
Findings
Discrepancies in $ m extOmega_{m0}$ and $H_0$ between high and low redshift bins.
Potential indication of deviations from standard $ m extLambda$CDM at different redshifts.
Future high-quality data could confirm these deviations as signs of new physics.
Abstract
Despite the broad successes of the flat CDM model and its fitness to the various cosmological observations, it confronts challenges stemming from anomalies in the measurements of the Hubble constant () and the amplitude of matter fluctuations (). These inconsistencies have necessitated a reassessment of the model parameters, with a particular focus on their potential dependence on redshift. This study pioneers a new investigation to probe this redshift dependency by generating mock data simulated from observational data of Type Ia supernovae (SNIa) and cosmic chronometers (CC), thereby increasing the data density in this field. By sorting the data into high-redshift and low-redshift bins, we aim to refine the cosmological constraints on the parameters of the CDM model and determine whether the noted dependence on redshift is due to a lack of…
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Taxonomy
TopicsComputational Physics and Python Applications
