Do equation of state parametrizations of dark energy faithfully capture the dynamics of the late universe?

TL;DR

This study compares different dark energy parametrizations and reconstructions to assess their ability to accurately capture late-universe dynamics, revealing method-dependent discrepancies at intermediate redshifts.

Contribution

It demonstrates that equation of state parametrizations may not fully capture complex dark energy behavior around redshift 1.7, highlighting limitations of smooth models.

Findings

Reconstruction favors stronger deceleration at z~1.7

EoS parametrizations often imply phantom-like behavior

Bayesian evidence prefers simpler parametric models

Abstract

We investigate how strongly late-time inferences about DE dynamics depend on the functional prior used to represent the expansion history. Using identical late-time combinations of CC, DESI BAO measurements, the Pantheon+ SN1a sample, and the H0DN prior, we compare a node-based reconstruction of the reduced Hubble function $E(z)$ with a representative family of smooth low-dimensional DE EoS parametrizations, including CPL. Over the redshift range constrained by the data, both approaches yield consistent $H(z)$, and, in the absence of H0DN, compatible values of $H_0$. However, a clear method dependence emerges at intermediate redshift ($z\sim1.7$): the reconstruction favors stronger deceleration, $q_{\rm Rec}(1.7)\simeq0.56-0.61$, whereas the smooth parametrizations cluster at $q(1.7)\simeq0.32-0.40$, implying a persistent $\sim2-3\sigma$ discrepancy across dataset combinations and parametrizations. For the EoS-based parametrizations, whose effective DE densities remain positive by construction, the preferred $w_{\rm DE}(1.7)<-1$ values correspond to NECB-violating (phantom-like) behaviour, but this is a less robust discriminator as $w_{\rm DE}$ becomes ill-conditioned as $\rho_{\rm DE}\to0$. In the effective-fluid mapping, the reconstruction accommodates the same late-time kinematical preference through a rapid descent of $\rho_{\rm DE}(z)$ toward very small values and a sign change, whereas the EoS-based parametrizations absorb it through smoother, and in several cases NECB-violating, evolution over $z\sim1-2$. Although the reconstruction improves the best-fit likelihood, especially with H0DN, Bayesian evidence continues to favor the simpler parametric descriptions. Our results isolate $z\sim1.5-2$ as the key window in which EoS-based DE parametrizations can compress localized kinematic structure and associated features of DE that are still permitted by current late-time data.