PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 28, 20260 citationsOpen Access

Observational Discriminant Between COCM and Alternative Dark Energy Models: A Comparison Using DESI DR2 and Cosmic Chronometer Data

View Full Paper
JGJosé Luis Vázquez González

Key Points

  • This study aims to compare the Concentric Orbital Cosmological Model (COCM) with alternative dark energy models, including mirage models, using observational data.
  • Expanded comparison of COCM against mirage models using 14 data points from DESI DR2 and cosmic chronometer datasets.
  • Evaluation of models based on statistical measures such as reduced chi-squared, AIC, BIC, and Bayesian evidence.
  • At current precision, COCM and mirage models are statistically indistinguishable (p-values from AIC, BIC comparisons).
  • COCM predicts a distinct second harmonic in the H(z) power spectrum at DESI DR3 precision, while mirage models do not.

Abstract

The Concentric Orbital Cosmological Model (COCM) parametrises the Hubble rate as an oscillatory modulation of the ΛCDM background at fixed frequency ωz = 11.1991. This paper extends the comparison of the COCM against alternative dark energy models to include the mirage class, which captures the DESI DR2 phenomenology with a single additional parameter and performance comparable to w₀ waCDM. With n = 14 data points, the COCM and mirage models are statistically indistinguishable at current precision, as measured by reduced χ²r, AIC, BIC, and Bayesian evidence. However, the two models make qualitatively distinct predictions at DESI DR3 precision: the COCM orbital structure predicts a second harmonic at 2ωz in the H(z) power spectrum, absent by construction in the mirage model and in smooth one-parameter parametrisations of w(z). This provides a falsifiable discriminant that can be tested directly with DR3 data.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

José Luis Vázquez González (2026) studied this question.

synapsesocial.com/papers/6a17dd4e3fad632b0f9da190https://doi.org/10.5281/zenodo.20387967
Ask AI
Helpful
Bookmark
Share
View Full Paper