Evaluating extensions to LCDM: an application of Bayesian model averaging and selection
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2024
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| author | Paradiso, S. McGee, G. Percival, W. J. |
| author_facet | Paradiso, S. McGee, G. Percival, W. J. |
| contents | 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 $Λ$CDM model, considering a varying curvature density parameter $Ω_{\rm k}$, 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 $Λ$CDM model is favoured when combining CMB data with CMB lensing, BAO and Bicep-KECK 2018 data against $K-Λ$CDM model $N_{\rm eff}-Λ$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 $Λ$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 $Λ$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 $Λ$CDM. Overall, we find that including the model uncertainty in the considered cases does not significantly impact the Hubble tension. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2403_02120 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Evaluating extensions to LCDM: an application of Bayesian model averaging and selection Paradiso, S. McGee, G. Percival, W. J. Cosmology and Nongalactic Astrophysics 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 $Λ$CDM model, considering a varying curvature density parameter $Ω_{\rm k}$, 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 $Λ$CDM model is favoured when combining CMB data with CMB lensing, BAO and Bicep-KECK 2018 data against $K-Λ$CDM model $N_{\rm eff}-Λ$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 $Λ$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 $Λ$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 $Λ$CDM. Overall, we find that including the model uncertainty in the considered cases does not significantly impact the Hubble tension. |
| title | Evaluating extensions to LCDM: an application of Bayesian model averaging and selection |
| topic | Cosmology and Nongalactic Astrophysics |
| url | https://arxiv.org/abs/2403.02120 |