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Impact of a negative cosmological constant on the reconstruction of dark energy in light of DESI BAO data

Hao Wang, Yun-Song Piao

TL;DR

The paper investigates whether a negative cosmological constant (NCC) can coexist with an evolving dark energy component in light of DESI BAO and Pantheon SN data. It employs two reconstruction strategies: a redshift-binned parameterization of the dark-energy EOS $w(z)$ and a non-parametric Gaussian Process (GP) approach, in a framework where $H(z)$ depends on $"Ω_m", "Ω_Λ", and the evolving component. Both methods find NCC mildly preferred (≈1σ) and show that degeneracies between $ ablaΩ_Λ$ and $w(z)$ weaken exact constraints on the evolution of dark energy, though the phantom divide $w=-1$ is more consistent with the 1σ posterior when NCC is included. The results imply NCC alone cannot resolve the Hubble tension but could be relevant with pre-recombination physics, and future DESI and Euclid data may confirm or tighten the NCC signal.

Abstract

An anti-de Sitter vacuum, corresponding to a negative cosmological constant (NCC), might coexist with one evolving positive dark energy component at low redshift and is hinted by the latest DESI observations. In this paper, we use two methods, \textit{redshift-binned} and \textit{Gaussian Process-based} reconstructions to investigate the effect of a NCC on the equation of state (EOS) $w(z)$ of evolving dark energy (DE) component. We find that a NCC is slightly preferred in both the two reconstructions by up to $\simeq1σ$. Although the degeneracy between the EOS of evolving DE component and NCC weakens the constraint on the reconstructed $w(z)$, this degeneracy leads to the phantom divide $w=-1$ more consistent with the 1$σ$ posterior of $w(z)$.

Impact of a negative cosmological constant on the reconstruction of dark energy in light of DESI BAO data

TL;DR

The paper investigates whether a negative cosmological constant (NCC) can coexist with an evolving dark energy component in light of DESI BAO and Pantheon SN data. It employs two reconstruction strategies: a redshift-binned parameterization of the dark-energy EOS and a non-parametric Gaussian Process (GP) approach, in a framework where depends on ablaΩ_Λw(z)w=-1$ is more consistent with the 1σ posterior when NCC is included. The results imply NCC alone cannot resolve the Hubble tension but could be relevant with pre-recombination physics, and future DESI and Euclid data may confirm or tighten the NCC signal.

Abstract

An anti-de Sitter vacuum, corresponding to a negative cosmological constant (NCC), might coexist with one evolving positive dark energy component at low redshift and is hinted by the latest DESI observations. In this paper, we use two methods, \textit{redshift-binned} and \textit{Gaussian Process-based} reconstructions to investigate the effect of a NCC on the equation of state (EOS) of evolving dark energy (DE) component. We find that a NCC is slightly preferred in both the two reconstructions by up to . Although the degeneracy between the EOS of evolving DE component and NCC weakens the constraint on the reconstructed , this degeneracy leads to the phantom divide more consistent with the 1 posterior of .
Paper Structure (6 sections, 3 equations, 5 figures, 2 tables)

This paper contains 6 sections, 3 equations, 5 figures, 2 tables.

Figures (5)

  • Figure 1: Reconstructed evolution of the redshift-binned dark energy equation-of-state parameter $w(z)$ from DESI+Pantheon data, with and without NCC respectively.
  • Figure 2: Reconstructed posteriors of the redshift-binned dark energy for BAO observables $r_dH(z)$ with and without NCC respectively. The reference model is the bestfit values of $w_0w_a$CDM in Wang:2024hwd.
  • Figure 3: Reconstructed evolution of the dark energy equation-of-state parameter $w(z)$ from DESI+Pantheon data, as well as that with fixed $H_0$ and extra $\Omega_\Lambda$ respectively.
  • Figure 4: Reconstructed posterior using squared exponential kernel for the expansion rate $E(z)$ relative to the reference model.
  • Figure 5: Reconstructed posteriors using squared exponential kernel for BAO observables $D_M(z)/r_d$, $D_H(z)/r_d$ and $D_V(z)/r_d$ for different models respectively.