Related papers: Data-driven model validation for neutrino-nucleus …
The interpretation of the signals detected by high precision experiments aimed at measuring neutrino oscillations requires an accurate description of the neutrino-nucleus cross sections. One of the key element of the analysis is the…
The NOMAD experiment collected valuable neutrino data samples, matching both the large statistics of massive calorimeters and the reconstruction quality of bubble chambers. This paper describes the recent measurements of neutrino…
Nuclear reaction data required for astrophysics and applications is incomplete, as not all nuclear reactions can be measured or reliably predicted. Neutron-induced reactions involving unstable targets are particularly challenging, but often…
We review coherent scattering of neutrinos on nuclei by coupling the weak currents to vector and axial-vector meson states. The couplings are obtained from known reactions, like $\tau$--lepton and vector meson decays. We compute and present…
The Standard Model (SM) of particle physics effectively explains most observed phenomena, though some anomalies, especially in the neutrino sector, suggest the need for extensions. In this Letter, we perform the first global fit of elastic…
The description of nuclear reactions induced by supernova neutrinos has witnessed significant progress during the recent years. At the energies and momentum transfers relevant for supernova neutrinos neutrino-nucleus cross sections are…
A new generation of neutrino cross-section experiments at the GeV scale is crucial in the precision era of oscillation physics and lepton flavor studies. In this document, we present a novel neutrino beam design that leverages the…
One of the challenges in twinned systems is ensuring the digital twin remains a valid representation of the system it twins. Depending on the type of twinning occurring, it is either trivial, such as in dashboarding/visualizations that…
Neutrino experiments are often limited by low statistics, sizable systematic uncertainties, and coarse observable binning, which can hinder discrimination among competing beyond-the-Standard-Model (BSM) explanations of anomalous signals. In…
It is shown that neutrino oscillation processes can be consistently described in the framework of quantum field theory. Namely, the oscillating electron survival probabilities in experiments with neutrino detection by charged-current and…
Monitoring the dynamics processes in combustors is crucial for safe and efficient operations. However, in practice, only limited data can be obtained due to limitations in the measurable quantities, visualization window, and temporal…
Research on accelerator driven systems (ADS), related new fuels and their ability for nuclear waste incineration has led to a revival of interest in nuclear cross sections of many nuclides over a large energy range. Discrepancies observed…
New neutrino interactions beyond the Standard Model (BSM) have been of much interest in not only particle physics but also cosmology and astroparticle physics. We numerically investigate the time delay distribution of astrophysical…
Two new facilities have recently been proposed to measure low energy neutrino-nucleus cross sections, the nu-SNS (Spallation Neutron Source) and low energy beta beams. The former produces neutrinos by pion decay at rest, while the latter…
Data driven transmission line fault location methods have the potential to more accurately locate faults by extracting fault information from available data. However, most of the data driven fault location methods in the literature are not…
Uncertainties in knowledge of neutrino interactions directly impact the ability to measure the parameters of neutrino oscillation. Experiments which make use of differing technologies and neutrino beams are sensitive to different…
Because experiment/model comparisons in magnetic confinement fusion have not yet satisfied the requirements for validation as understood broadly, a set of approaches to validating mathematical models and numerical algorithms are recommended…
In the context of model-based control of industrial processes, it is a common practice to develop a data-driven linear dynamical model around a specified operating point. However, in applications involving wider operating conditions,…
In a regression context, when the relevant subset of explanatory variables is uncertain, it is common to use a data-driven model selection procedure. Classical linear model theory, applied naively to the selected sub-model, may not be valid…
Deep neural networks provide flexible frameworks for learning data representations and functions relating data to other properties and are often claimed to achieve 'super-human' performance in inferring relationships between input data and…