CMB distance priors revisited: effects of dark energy dynamics, spatial curvature, primordial power spectrum, and neutrino parameters
Zhongxu Zhai, Chan-Gyung Park, Yun Wang, Bharat Ratra

TL;DR
This paper evaluates the robustness of CMB distance priors across different cosmological models, including dark energy, curvature, primordial spectrum variations, and neutrino parameters, providing an updated set of priors for diverse cosmologies.
Contribution
It offers an expanded and refined set of CMB distance priors that accurately reproduce full CMB constraints across various cosmological models, including non-standard scenarios.
Findings
CMB distance priors are reliable for dark energy models with standard primordial spectra.
Non-flat models with untilted primordial spectra challenge the reliability of shift parameters.
Including neutrino parameters like $ u$ mass and $N_{eff}$ is essential for accurate CMB data constraints.
Abstract
As a physical and sufficient compression of the full CMB data, the CMB distance priors, or shift parameters, have been widely used and provide a convenient way to include CMB data when obtaining cosmological constraints. In this paper, we revisit this data vector and examine its stability under different cosmological models. We find that the CMB distance priors are an accurate substitute for the full CMB data when probing dark energy dynamics. This is true when the primordial power spectrum model is directly generalized from the power spectrum of the model used in the derivation of the distance priors from the CMB data. We discover a difference when a non-flat model with the untilted primordial inflation power spectrum is used to measure the distance priors. This power spectrum is a radical change from the more conventional tilted primordial power spectrum and violates fundamental…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
