Related papers: On the Bayesian approach to neutrino mass ordering
We review the current status of the neutrino mass and mixing parameters needed to reconstruct the neutrino mass matrix. A comparative study of the precision in the measurement of oscillation parameters expected from the next generation…
Bayesian optimisation is a powerful tool to solve expensive black-box problems, but fails when the stationary assumption made on the objective function is strongly violated, which is the case in particular for ill-conditioned or…
We study the constraints on neutrino masses that could be derived from the observation of a Galactic supernova neutrino signal with present and future neutrino detectors. Our analysis is based on a recently proposed method that uses the…
The flagship measurement of the JUNO experiment is the determination of the neutrino mass ordering. Here we revisit its prospects to make this determination by 2030, using the current global knowledge of the relevant neutrino parameters as…
We have previously reported a Bayesian algorithm for determining the coordinates of points in three-dimensional space from uncertain constraints. This method is useful in the determination of biological molecular structure. It is limited,…
There are several assumptions made in a standard $\chi^2$ analysis of data, including the frequent assumption that the likelihood function is well approximated by a multivariate Gaussian distribution. This article briefly reviews the…
Neutrino physics is nowadays receiving more and more attention as a possible source of information for the long--standing investigation of new physics beyond the Standard Model. The rather recent measurement of the third mixing angle…
Oscillation experiments show that neutrinos have masses. They however only determine the neutrinop mass differences. Information on the absolute masses can be obtained by studying the kinematics in weak decays, or by searching for…
The measurement of the efficiency of an event selection is always an important part of the analysis of experimental data. The statistical techniques which are needed to determine the efficiency and its uncertainty are reviewed. Frequentist…
In this paper the Bayesian analysis is applied to assign a probability density to the value of a quantity having a definite sign. This analysis is logically consistent with the results, positive or negative, of repeated measurements.…
Current analysis of astronomical data are confronted with the daunting task of modeling the awkward features of astronomical data, among which heteroscedastic (point-dependent) errors, intrinsic scatter, non-ignorable data collection…
We discuss to what extent future precision measurements of neutrino mixing observables will influence the information we can draw from a measurement of (or an improved limit on) neutrinoless double beta decay. Whereas the Delta m^2…
Over the past few decades, outstanding progress in the neutrino experiment frontier has greatly advanced our understanding of the flavor oscillations of active neutrinos. The remaining key questions such as the neutrino mass ordering, the…
Neutrino masses are yet unknown. We discuss the present state of effective electron anti-neutrino mass from $\beta$ decay experiments; effective Majorana neutrino mass from neutrinoless double-beta decay experiments; neutrino mass squared…
We present updated values for the mass-mixing parameters relevant to neutrino oscillations, with particular attention to emerging hints in favor of theta_13>0. We also discuss the status of absolute neutrino mass observables, and a possible…
The neutron star equation of state is now being constrained from a diverse set of multi-messenger data, including gravitational waves from binary neutron star mergers, X-ray observations of the neutron star radius, and many types of…
We consider how well current theories can predict neutrino mass and mixing parameters, and construct a statistical discriminator which allows us to compare different models to each other. As an example we consider see-saw models based on…
Recently it has been proposed, in the context of experiments designed to resolve the neutrino mass hierarchy, to use the average posterior probability of one of the hypotheses as a measure of sensitivity of future experiments. This has led…
The ranking problem is to order a collection of units by some unobserved parameter, based on observations from the associated distribution. This problem arises naturally in a number of contexts, such as business, where we may want to rank…
This paper explores Bayesian estimation for categorical data, focusing on simple yet effective models that provide a foundation for applying more advanced methods accurately and reliably in real-world applications. We begin by revisiting…