{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/evaluating-extensions-to-lcdm-an-application","title":"Evaluating extensions to LCDM: an application of Bayesian model averaging and selection","arxiv_id":"2403.02120","date":"2024-03-04","proceeding":null,"authors":["S. Paradiso","G. McGee","W. J. Percival"],"abstract":"We employ Bayesian Model Averaging (BMA) as a powerful statistical framework to address key cosmological questions about the universe's fundamental properties. We explore extensions beyond the standard $\\Lambda$CDM model, considering a varying curvature density parameter $\\Omega_{\\rm k}$, a spectral index $\\mathrm{n}_{\\rm s}=1$ and a varying $n_{\\rm run}$, a constant dark energy equation of state (EOS) $w_0$CDM and a time-dependent one $w_0w_a$CDM. We also test cosmological data against a varying effective number of neutrino species $N_{\\rm eff}$. Data from different combinations of cosmic microwave background (CMB) data from the last Planck PR4 analysis, CMB lensing from Planck 2018, baryonic acoustic oscillations (BAO) and the Bicep-KECK 2018 results, are used. We find that the standard $\\Lambda$CDM model is favoured when combining CMB data with CMB lensing, BAO and Bicep-KECK 2018 data against $K-\\Lambda$CDM model $N_{\\rm eff}-\\Lambda$CDM with a probability $> 80\\%$. When investigating the dark energy EOS, we find that this dataset is not able to express a strong preference between the standard $\\Lambda$CDM model and the constant dark energy EOS model $w_0$CDM, with an approximately split model posterior probability of $\\approx 60\\%:40\\%$ in favour of $\\Lambda$CDM, whereas the time-varying dark energy EOS model is ruled out. Finally, we find that the CMB data alone show a strong preference for a model that includes the running of the spectral index $n_{\\rm run}$, with a probability $\\approx 90\\%$, when compared to the $n_{\\rm s}=1$ model and the standard $\\Lambda$CDM. Overall, we find that including the model uncertainty in the considered cases does not significantly impact the Hubble tension.","url_abs":"https://arxiv.org/abs/2403.02120v4","url_pdf":"https://arxiv.org/pdf/2403.02120v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"evaluating-extensions-to-lcdm-an-application","repo_url":"https://github.com/simonpara/fast-mpc","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}