Generalizing thawing dark energy models: the standard vis-\`a-vis model independent diagnostics
Debabrata Adak, Debasish Majumdar, Supratik Pal

TL;DR
This paper introduces a two-parameter generalization of the dark energy equation of state for thawing models, compares it with observational data, and identifies model-independent diagnostics that can distinguish different thawing dark energy models.
Contribution
The paper proposes a new generalized EOS for thawing dark energy models and highlights diagnostics that effectively differentiate models beyond standard observables.
Findings
Phantom type of thawing dark energy is favored up to 2σ confidence.
Different thawing models are indistinguishable using standard parameters but can be distinguished using model-independent diagnostics.
Model-independent parameters like {r,s,Om3} effectively discriminate between thawing dark energy models.
Abstract
We propose a two parameter generalization for the dark energy equation of state (EOS) for thawing dark energy models which includes PNGB, CPL and Algebraic thawing models as limiting cases and confront our model with the latest observational data namely SNe Ia, OHD, CMB, BOSS data. Our analysis reveals that the phantom type of thawing dark energy is favoured upto confidence level. These results also show that thawing dark energy EOS is not unique from observational point of view. Though different thawing dark energy models are not distinguishable from each other from best-fit values (upto C.L.s) of matter density parameter () and hubble parameter () at present epoch, best-fit plots of linear growth of matter perturbation () and average deceleration parameter (); the difference indeed reflects in best-fit variations of thawing…
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