Assessing the consistency of the CPL dark-energy model with cosmological data: Simulation-calibrated neural posterior disagreement
Abstract
Recent DESI observations hint at a preference for dynamical dark energy with an equation of state that crosses the phantom divide within the Chevallier-Polarski-Linder (CPL) parameterization. In this work, we assess the consistency of the CPL parameterization with current cosmological observations. We develop a model check based on the disagreement between posteriors inferred by neural posterior estimation and flow-matching posterior estimation. Both estimators are trained on the same CPL simulations, and their posterior disagreement is calibrated using independent simulations to obtain a global p-value. Controlled simulations assess the reliability of the calibrated p-values and show how detection sensitivity depends on the form of departure from the assumed model. Applying the test to the compressed CMB+DESI+DESY5 data vector yields pglobal=0.524, indicating that the current observations are consistent with the CPL model. The method has a median evaluation time of only 0.53 s, enabling efficient assessments of cosmological model adequacy. This framework enables efficient tests of dark-energy models, providing a firmer basis for investigating the physical origin of cosmic acceleration.
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BibTeX
@misc{sun2026assessing,
title = {{Assessing the consistency of the CPL dark-energy model with cosmological data: Simulation-calibrated neural posterior disagreement}},
author = {Tian-Yang Sun and Tian-Nuo Li and Guo-Hong Du and He Wang and Jing-Fei Zhang and Xin Zhang},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.31044},
eprint = {2610.31044},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.31044},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Assessing the consistency of the CPL dark-energy model with cosmological data: Simulation-calibrated neural posterior disagreement
AU - Tian-Yang Sun
AU - Tian-Nuo Li
AU - Guo-Hong Du
AU - He Wang
AU - Jing-Fei Zhang
AU - Xin Zhang
PY - 2026
DA - 2026/10/22
PB - arXiv
DO - 10.48550/arxiv.2610.31044
UR - https://arxiv.org/abs/2610.31044
AB - Recent DESI observations hint at a preference for dynamical dark energy with an equation of state that crosses the phantom divide within the Chevallier-Polarski-Linder (CPL) parameterization. In this work, we assess the consistency of the CPL parameterization with current cosmological observations. We develop a model check based on the disagreement between posteriors inferred by neural posterior estimation and flow-matching posterior estimation. Both estimators are trained on the same CPL simulations, and their posterior disagreement is calibrated using independent simulations to obtain a global p-value. Controlled simulations assess the reliability of the calibrated p-values and show how detection sensitivity depends on the form of departure from the assumed model. Applying the test to the compressed CMB+DESI+DESY5 data vector yields p_global=0.524, indicating that the current observations are consistent with the CPL model. The method has a median evaluation time of only 0.53 s, enabling efficient assessments of cosmological model adequacy. This framework enables efficient tests of dark-energy models, providing a firmer basis for investigating the physical origin of cosmic acceleration.
ER -