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Gariazzo, S., Gerbino, M., Brinckmann, T., Lattanzi, M., Mena, O., Schwetz, T., et al. (2022). Neutrino mass and mass ordering: no conclusive evidence for normal ordering. J. Cosmol. Astropart. Phys., 10(10), 010–18pp.
Abstract: The extraction of the neutrino mass ordering is one of the major challenges in particle physics and cosmology, not only for its implications for a fundamental theory of mass generation in nature, but also for its decisive role in the scale of future neutrinoless double beta decay experimental searches. It has been recently claimed that current oscillation, beta decay and cosmological limits on the different observables describing the neutrino mass parameter space provide robust decisive Bayesian evidence in favor of the normal ordering of the neutrino mass spectrum [1]. We further investigate these strong claims using a rich and wide phenomenology, with different sampling techniques of the neutrino parameter space. Contrary to the findings of Jimenez et al. [1], no decisive evidence for the normal mass ordering is found. Neutrino mass ordering analyses must rely on priors and parameterizations that are ordering-agnostic: robust results should be regarded as those in which the preference for the normal neutrino mass ordering is driven exclusively by the data, while we find a difference of up to a factor of 33 in the Bayes factors among the different priors and parameterizations exploited here. An ordering-agnostic prior would be represented by the case of parameterizations sampling over the two mass splittings and a mass scale, or those sampling over the individual neutrino masses via normal prior distributions only. In this regard, we show that the current significance in favor of the normal mass ordering should be taken as 2.7 sigma (i.e. moderate evidence), mostly driven by neutrino oscillation data. Let us stress that, while current data favor NO only mildly, we do not exclude the possibility that this may change in the future. Eventually, upcoming oscillation and cosmological data may (or may not) lead to a more significant exclusion of IO.
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Raffaelli, A., Ballardini, M., & Barbieri, N. (2026). Signals from the early Universe: a comprehensive search for primordial features in Planck CMB datasets. J. Cosmol. Astropart. Phys., (10), 024–48pp.
Abstract: We investigate the presence of primordial oscillatory features in measurements of cosmic microwave background (CMB) anisotropies through a systematic comparison of phenomenological templates. Building upon previous searches for primordial features using Planck data, we compare the full PR3 legacy release with the PR4 (NPIPE) processing to assess how the results depend on the choice of CMB maps and likelihood framework. To maximise our sensitivity to rapidly varying oscillatory signals, we employ unbinned likelihoods. We find that several previously reported indications of oscillatory structure persist across different analyses, although none attains global statistical significance. Furthermore, some anomalies reported in earlier studies are substantially reduced when updated to the new versions of the CamSpec likelihood using Planck PR4 products. For all templates considered, we identify a small number of frequencies in the range omega similar to 10-100 that improve the fit to the CMB data by up to triangle chi 2 similar or equal to -10 to-15 relative to the featureless reference model. However, this improvement is not supported by a Bayesian model comparison, as the Bayes factor consistently does not favour the extended models. The inclusion of three or four additional parameters can reduces the overall predictability of the feature models and leads to an Occam penalty. Finally, after properly accounting for the look-elsewhere effect, the significance of the preferred frequencies is reduced, corresponding to a global statistical significance of at most 2.6 sigma. Finally, we present forecasts for forthcoming CMB experiments, highlighting the decisive role of next-generation polarisation measurements in distinguishing genuine primordial oscillations from statistical fluctuations and modelling systematics. The upper bounds or uncertainties on the feature amplitudes, expected from the combination of Simons Observatory and LiteBIRD, improve by more than one order of magnitude.
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