Bayesian and frequentist constraints on dark energy parameterizations using non-CMB data
Abstract
Data from the Dark Energy Spectroscopic Instrument (DESI) BAO combined with the cosmic microwave background (CMB) have provided evidence for dynamical dark energy (DDE) with a phantom crossing (w(z) < −1) when constraining w0−wa parameterizations. Given the tension between BAO and CMB data within ΛCDM, we use only non-CMB data: Type Ia Supernovae (SNe) from the DES-Dovekie compilation, DESI BAO DR2, Gamma-Ray Bursts (GRBs) and Redshift-Space-Distortion (RSD) measurements. We use the dataset combinations GRB+BAO, BAO+SNe and GRB+BAO+SNe, each with RSD. We perform both Bayesian and frequentist analyses of two quintessence-inspired thawing dark energy parameterizations: the thawing quintessence parameterization (TQD) and the Algebraic Thawing parameterization (AT), together with the Chevallier-Polarski-Linder (CPL) and the Generalized Emergent Dark Energy parameterizations (GEDE). The GRB sample, used in this work, contributes only marginally to the constraints, while SNe tighten them considerably. The CPL equation of state shows a phantom crossing at z∼ 0.5, while TQD and AT improve the best-fit χ2 over ΛCDM, without showing phantom crossing. When SNe are included, TQD is preferred by the Bayes factor (moderately), AIC and DIC (positively). For CPL and AT, AIC and DIC prefer the extended model positively, while the Bayes factor weakly prefers ΛCDM over CPL and is inconclusive for AT. This difference is consistent with the Occam penalty from the prior volume in the Bayes factor. GEDE, with the DE density restricted to be suppressed at high redshifts is disfavored by all three metrics. Hence, the preference for DDE depends on the parameterization, the dataset and the comparison metric used.
Related
- Bayesian and frequentist perspectives agree on dynamical dark energy
- Comparing Mass-Varying Neutrino Dark Energy Models with DESI DR2: Cosmological Constraints and Bayesian Evidence
- A unified cosmographic reconstruction of the Hubble expansion: Bayesian constraints on dark energy and modified-gravity diagnostics
- Examining the Linear and Quadratic Dark Energy Parameterizations with DESI DR2 via AIC and BIC Selection
- Constraints on coupled dark energy in the DESI era
BibTeX
@misc{barua2026bayesian,
title = {{Bayesian and frequentist constraints on dark energy parameterizations using non-CMB data}},
author = {Shubham Barua and Ansh Chandrakar and Shantanu Desai},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.01505},
eprint = {2611.01505},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.01505},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Bayesian and frequentist constraints on dark energy parameterizations using non-CMB data
AU - Shubham Barua
AU - Ansh Chandrakar
AU - Shantanu Desai
PY - 2026
DA - 2026/11/01
PB - arXiv
DO - 10.48550/arxiv.2611.01505
UR - https://arxiv.org/abs/2611.01505
AB - Data from the Dark Energy Spectroscopic Instrument (DESI) BAO combined with the cosmic microwave background (CMB) have provided evidence for dynamical dark energy (DDE) with a phantom crossing (w(z) < −1) when constraining w_0−w_a parameterizations. Given the tension between BAO and CMB data within ΛCDM, we use only non-CMB data: Type Ia Supernovae (SNe) from the DES-Dovekie compilation, DESI BAO DR2, Gamma-Ray Bursts (GRBs) and Redshift-Space-Distortion (RSD) measurements. We use the dataset combinations GRB+BAO, BAO+SNe and GRB+BAO+SNe, each with RSD. We perform both Bayesian and frequentist analyses of two quintessence-inspired thawing dark energy parameterizations: the thawing quintessence parameterization (TQD) and the Algebraic Thawing parameterization (AT), together with the Chevallier-Polarski-Linder (CPL) and the Generalized Emergent Dark Energy parameterizations (GEDE). The GRB sample, used in this work, contributes only marginally to the constraints, while SNe tighten them considerably. The CPL equation of state shows a phantom crossing at z∼ 0.5, while TQD and AT improve the best-fit χ^2 over ΛCDM, without showing phantom crossing. When SNe are included, TQD is preferred by the Bayes factor (moderately), AIC and DIC (positively). For CPL and AT, AIC and DIC prefer the extended model positively, while the Bayes factor weakly prefers ΛCDM over CPL and is inconclusive for AT. This difference is consistent with the Occam penalty from the prior volume in the Bayes factor. GEDE, with the DE density restricted to be suppressed at high redshifts is disfavored by all three metrics. Hence, the preference for DDE depends on the parameterization, the dataset and the comparison metric used.
ER -