Related papers: Neutrino Oscillation Parameter Estimation Using St…
A consistent description of neutrino oscillations requires either the quantum-mechanical (QM) wave packet approach or a quantum field theoretic (QFT) treatment. We compare these two approaches to neutrino oscillations and discuss the…
In the last decades, a very important breakthrough has been brought in the elementary particle physics by the discovery of the phenomenon of the neutrino oscillations, which has shown neutrino properties beyond the Standard Model. But a…
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…
Neutrino oscillations are studied employing sources of low energy monoenergetic neutrinos following electron capture by the nucleus and measuring electron recoils. Since the neutrino energy is very low the oscillation length appearing in…
Matter effects modify the mixing and the effective masses of neutrinos in a way which depends on the neutrino mass hierarchy. Consequently, for normal and inverted hierarchies the oscillations and flavor conversion results are different.…
Neural networks predictions are unreliable when the input sample is out of the training distribution or corrupted by noise. Being able to detect such failures automatically is fundamental to integrate deep learning algorithms into robotics.…
Probabilistic prediction of sequences from images and other high-dimensional data is a key challenge, particularly in risk-sensitive applications. In these settings, it is often desirable to quantify the uncertainty associated with the…
This work proposes a general framework for capturing noise-driven transitions in spatially extended non-equilibrium systems and explains the emergence of coherent patterns beyond the instability onset. The framework relies on stochastic…
The analogy between supersymmetric quantum mechanics and matter-enhanced neutrino oscillations is exploited to obtain exact solutions for a class of electron density profiles. This integrability condition is analogous to the…
Several new and interesting aspects of neutrino oscillations in a magnetic field are considered: 1) We develop a standard usually used approach to the neutrino spin oscillations in the neutrino mass basis and obtain the effective neutrino…
We study neutrino oscillations in space within a realistic model in which both the source and the target are considered to be stationary having Gaussian-form localizations. The model admits an exact analytic solution in field theory which…
Motivated by recent results from SuperKamiokande, we study both solar and atmospheric neutrino fluxes in the context of oscillations of the three known neutrinos. We aim at a global view which identifies the various possibilities, rather…
Accelerator-based neutrino oscillation experiments have the potential to revolutionise our understanding of fundamental physics, offering an opportunity to characterise charge-parity violation in the lepton sector; to determine the neutrino…
We present a general formalism for extracting information on the fundamental parameters associated with neutrino masses and mixings from two or more long baseline neutrino oscillation experiments. This formalism is then applied to the…
We propose a new pattern of the neutrino mixing matrix which can be parametrized as the product of an arbitrary Hermitian matrix and the well-known tri-bimaximal mixing matrix. In this scenario, nontrivial values of the smallest neutrino…
Online map generation and trajectory prediction are critical components of the autonomous driving perception-prediction-planning pipeline. While modern vectorized mapping models achieve high geometric accuracy, they typically treat map…
Neutrinos are neutral, spin-$\frac{1}{2}$ particles which undergo only weak interactions. The experimentally observed phenomenon of neutrino oscillation establishes the fact that neutrinos are massive and there is mixing between different…
We present a neural net algorithm for parameter estimation in the context of large cosmological data sets. Cosmological data sets present a particular challenge to pattern-recognition algorithms since the input patterns (galaxy redshift…
The vibrational behavior of molecules serves as a crucial fingerprint of their structure, chemical state, and surrounding environment. Neutron vibrational spectroscopy provides comprehensive measurements of vibrational modes without…
We present a new approach to the analysis of neutrino oscillation experiments, in the one mass-scale limit of the three-generation scheme. In this framework we reanalyze and recombine the most constraining accelerator and reactor data, in…