相关论文: On the Bayesian approach to neutrino mass ordering

A recent neutrino experiment at Daya Bay gives superior data of the distribution of the prompt energy. In this paper, the energy distribution presented in the experiment is simulated by applying a Gaussian-like packet to the neutrino wave…

A Bayesian filtering algorithm is developed for a class of state-space systems that can be modelled via Gaussian mixtures. In general, the exact solution to this filtering problem involves an exponential growth in the number of mixture…

Bayesian statistics is based on the subjective definition of probability as {\it ``degree of belief''} and on Bayes' theorem, the basic tool for assigning probabilities to hypotheses combining {\it a priori} judgements and experimental…

Recent (first or/and the best) results from the neutrino experiments are reviewed and their implications for the theory are discussed. The sense of the experiments is the searching for neutrino masses, mixing and interactions beyond the…

We consider discrete nonparametric priors which induce Gibbs-type exchangeable random partitions and investigate their posterior behavior in detail. In particular, we deduce conditional distributions and the corresponding Bayesian…

We study the sensitivity to neutrino masses of a Galactic supernova neutrino signal as could be measured with the detectors presently in operation and with future large volume water \v{C}erencov and scintillator detectors. The analysis uses…

We investigate the potential of short-baseline experiments in order to measure the dispersion relation of the (muon) neutrino, with a prospect of eventually measuring the neutrino mass. As a byproduct, the experiment would help to constrain…

We want to select the best systems out of a given set of systems (or rank them) with respect to their expected performance. The systems allow random observations only and we assume that the joint observation of the systems has a…

The various mechanisms for neutrinoless double beta decay in gauge theories are reviewed and the present experimental data is used to set limits on physics scenarios beyond the standard model. The positive indications for nonzero neutrino…

As commonly understood, the noise spectroscopy problem---characterizing the statistical properties of a noise process affecting a quantum system by measuring its response---is ill-posed. Ad-hoc solutions assume implicit structure which is…

The relatively large value of $\theta_{13}$ established recently by the Daya Bay reactor experiment opens the possibility to determine the neutrino mass ordering with experiments currently under construction. We investigate synergies…

Bayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model…

Bayesian coresets have emerged as a promising approach for implementing scalable Bayesian inference. The Bayesian coreset problem involves selecting a (weighted) subset of the data samples, such that the posterior inference using the…

This work proposes a Bayesian inference method for the reduced-order modeling of time-dependent systems. Informed by the structure of the governing equations, the task of learning a reduced-order model from data is posed as a Bayesian…

I review promising approaches to neutrino mass models, focussing on three neutrino patterns of neutrino masses and mixing angles, and the corresponding Majorana mass matrices. I discuss the see-saw mechanism, and show how it may be applied…

In this contribution, we briefly present the equation-of-state modelling for application to neutron stars and discuss current constraints coming from nuclear physics theory and experiments. To assess the impact of model uncertainties, we…

We consider the Bayesian optimal filtering problem: i.e. estimating some conditional statistics of a latent time-series signal from an observation sequence. Classical approaches often rely on the use of assumed or estimated transition and…

We review some fundamental aspects of the theory of neutrino masses and mixing. The results of neutrino oscillation experiments are interpreted as evidence of three-neutrino mixing. Implications for the mixing parameters and the neutrino…

We point out that leptonic weak-basis invariants are an important tool for the study of the properties of lepton flavour models. In particular, we show that appropriately chosen invariants can give a clear indication of whether a particular…

We propose an analytical solution to the on-off problem within the framework of Bayesian statistics. Both the statistical significance for the discovery of new phenomena and credible intervals on model parameters are presented in a…