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Dynamical Dark Energy Signatures from a New Transition $Om(z)$ Parametrization in Flat FLRW Cosmology

Manish Yadav, Archana Dixit, Anirudh Pradhan, M. S. Barak

TL;DR

This work introduces a new transition form for the Om(z) diagnostic, $Om(z) = \frac{z^l}{(1+z)^m}$, within a flat FLRW cosmology to probe dynamical dark energy. By constraining $H_0$, $l$, and $m$ with observational data from OHD, PP, and PP&SH0ES via MCMC, the authors uncover dataset-dependent transition redshifts signaling a phantom-to-quintessence evolution and achieve H0 values consistent with SH0ES, thereby alleviating part of the Planck–SH0ES tension. The analysis also provides estimates for the universe's age and the epoch of cosmic acceleration, with model selection indicating competitive performance relative to ΛCDM. Overall, the transition Om(z) parameterization offers a flexible framework for interpolating cosmological evolution across epochs and testing dynamical dark energy against multiple data sets.

Abstract

We investigate a cosmic scenario using a new transition parameterization of the $Om(z)$ diagnostic, $Om(z) = \frac{z^l}{(1+z)^m}$, in the spatially flat Friedmann Lemaître Robertson-Walker (FLRW) framework. Using observational datasets such as Observational Hubble Data (OHD), Pantheon Plus (PP), and SH0ES, we analyze the evolution of the $Om(z)$ function to probe deviations from the standard $Λ$CDM model and constrain free parameter space {$H_0$, l, m } using Markov Chain Monte Carlo (MCMC) analysis with the emcee sampler. Our analysis reveals a clear transition in the slope of $Om(z)$ from negative to positive at transition redshift values $z_t \approx 1.41$, $0.65$, and $0.33$ for the OHD, OHD+PP, and OHD+PP$\&$SH0ES datasets, respectively. This behavior suggests a dynamical evolution of dark energy, indicating a transition from a quintessence-like phase to a phantom regime. From the combined OHD+PP$\&$SH0ES dataset, we obtain a best-fit value of the Hubble constant \( H_0 = 73.01 \pm 0.36 \, \mathrm{km\,s^{-1}\,Mpc^{-1}} \), which is consistent with the SH0ES calibration and supports the viability of our model. Additionally, our analysis indicates that the current age of the Universe is approximately $13 \sim 14$ Gyr from all available combinations of datasets, which is consistent with observational expectations. Further, we find that the deceleration-to-acceleration transition, which marks the beginning of cosmic acceleration, is inferred to occur within the redshift interval $z_t \in [0.5, 0.8]$, highlighting the emergence of dark energy as the dominant component in the Universe's recent expansion history. Our transition $Om(z)$ parameterization captured progressive cosmological changes and enabled seamless interpolation over cosmic epochs.

Dynamical Dark Energy Signatures from a New Transition $Om(z)$ Parametrization in Flat FLRW Cosmology

TL;DR

This work introduces a new transition form for the Om(z) diagnostic, , within a flat FLRW cosmology to probe dynamical dark energy. By constraining , , and with observational data from OHD, PP, and PP&SH0ES via MCMC, the authors uncover dataset-dependent transition redshifts signaling a phantom-to-quintessence evolution and achieve H0 values consistent with SH0ES, thereby alleviating part of the Planck–SH0ES tension. The analysis also provides estimates for the universe's age and the epoch of cosmic acceleration, with model selection indicating competitive performance relative to ΛCDM. Overall, the transition Om(z) parameterization offers a flexible framework for interpolating cosmological evolution across epochs and testing dynamical dark energy against multiple data sets.

Abstract

We investigate a cosmic scenario using a new transition parameterization of the diagnostic, , in the spatially flat Friedmann Lemaître Robertson-Walker (FLRW) framework. Using observational datasets such as Observational Hubble Data (OHD), Pantheon Plus (PP), and SH0ES, we analyze the evolution of the function to probe deviations from the standard CDM model and constrain free parameter space {, l, m } using Markov Chain Monte Carlo (MCMC) analysis with the emcee sampler. Our analysis reveals a clear transition in the slope of from negative to positive at transition redshift values , , and for the OHD, OHD+PP, and OHD+PPSH0ES datasets, respectively. This behavior suggests a dynamical evolution of dark energy, indicating a transition from a quintessence-like phase to a phantom regime. From the combined OHD+PPSH0ES dataset, we obtain a best-fit value of the Hubble constant , which is consistent with the SH0ES calibration and supports the viability of our model. Additionally, our analysis indicates that the current age of the Universe is approximately Gyr from all available combinations of datasets, which is consistent with observational expectations. Further, we find that the deceleration-to-acceleration transition, which marks the beginning of cosmic acceleration, is inferred to occur within the redshift interval , highlighting the emergence of dark energy as the dominant component in the Universe's recent expansion history. Our transition parameterization captured progressive cosmological changes and enabled seamless interpolation over cosmic epochs.
Paper Structure (5 sections, 21 equations, 8 figures, 1 table)

This paper contains 5 sections, 21 equations, 8 figures, 1 table.

Figures (8)

  • Figure 1: Evolution of the diagnostic function $Om(z)$ for different dark-energy models. The purple curve ($l>m$) corresponds to a phantom model with a positive slope, the green curve ($l<m$) shows mixed phantom and quintessence behavior, and the red curve ($l=0,m>0$) represents a quintessence model with a negative slope. The dashed horizontal line marks a constant reference value of $Om(z)$.
  • Figure 2: The red curve for our model and black dotted line for $\Lambda$CDM model with error bar (blue colour).
  • Figure 3: The 2D plot shows the distance modulus $µ(z)$ for our model (red line) and the $\Lambda$CDM model (black dotted line) with corresponding blue colour error bars.
  • Figure 4: The reconstructed trajectories (from present to past) of $Om(z)$ diagnostic in our model based on the given datasets.
  • Figure 5: The triangular plot with $1\sigma$ and $2\sigma$ confidence levels for our model based on OHD+PP datasets.
  • ...and 3 more figures