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A novel approach to quantifying the sensitivity of current and future cosmological datasets to the neutrino mass ordering through Bayesian hierarchical modeling
Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Stockholm University, Nordic Institute for Theoretical Physics (Nordita). University of Michigan, USA.
Number of Authors: 42017 (English)In: Physics Letters B, ISSN 0370-2693, E-ISSN 1873-2445, Vol. 775, p. 239-250Article in journal (Refereed) Published
Abstract [en]

We present a novel approach to derive constraints on neutrino masses, as well as on other cosmological parameters, from cosmological data, while taking into account our ignorance of the neutrino mass ordering. We derive constraints from a combination of current as well as future cosmological datasets on the total neutrino mass M-nu and on the mass fractions f(nu),i = m(i)/M-nu (where the index i = 1, 2, 3 indicates the three mass eigenstates) carried by each of the mass eigenstates m(i), after marginalizing over the (unknown) neutrino mass ordering, either normal ordering (NH) or inverted ordering (IH). The bounds on all the cosmological parameters, including those on the total neutrino mass, take therefore into account the uncertainty related to our ignorance of the mass hierarchy that is actually realized in nature. This novel approach is carried out in the framework of Bayesian analysis of a typical hierarchical problem, where the distribution of the parameters of the model depends on further parameters, the hyperparameters. In this context, the choice of the neutrino mass ordering is modeled via the discrete hyperparameter h(type), which we introduce in the usual Markov chain analysis. The preference from cosmological data for either the NH or the IH scenarios is then simply encoded in the posterior distribution of the hyper-parameter itself. Current cosmic microwave background (CMB) measurements assign equal odds to the two hierarchies, and are thus unable to distinguish between them. However, after the addition of baryon acoustic oscillation (BAO) measurements, a weak preference for the normal hierarchical scenario appears, with odds of 4 : 3 from Planck temperature and large-scale polarization in combination with BAO (3 : 2 if small-scale polarization is also included). Concerning next-generation cosmological experiments, forecasts suggest that the combination of upcoming CMB (COrE) and BAO surveys (DESI) may determine the neutrino mass hierarchy at a high statistical significance if the mass is very close to the minimal value allowed by oscillation experiments, as for NH and a fiducial value of M-nu = 0.06 eV there is a 9 : 1 preference of normal versus inverted hierarchy. On the contrary, if the sum of the masses is of the order of 0.1 eV or larger, even future cosmological observations will be inconclusive. The innovative statistical strategy exploited here represents a very simple, efficient and robust tool to study the sensitivity of present and future cosmological data to the neutrino mass hierarchy, and a sound competitor to the standard Bayesian model comparison. The unbiased limit on M-nu we obtain is crucial for ongoing and planned neutrinoless double beta decay searches.

Place, publisher, year, edition, pages
2017. Vol. 775, p. 239-250
National Category
Physical Sciences
Identifiers
URN: urn:nbn:se:su:diva-150979DOI: 10.1016/j.physletb.2017.10.052ISI: 000417190700033OAI: oai:DiVA.org:su-150979DiVA, id: diva2:1173382
Available from: 2018-01-12 Created: 2018-01-12 Last updated: 2018-01-12Bibliographically approved

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Gerbino, MartinaFreese, Katherine
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