Related papers: A Review on Machine Learning for Neutrino Experime…
Machine learning has had an enormous impact in many scientific disciplines. Also in the field of low-temperature plasma modeling and simulation it has attracted significant interest within the past years. Whereas its application should be…
We review the theory and phenomenology of neutrino electromagnetic interactions, which give us powerful tools to probe the physics beyond the Standard Model. After a derivation of the general structure of the electromagnetic interactions of…
Our present knowledge of neutrinos can be summarized in terms of the "standard neutrino scenario". Phenomenology of this scenario as well as attempts to uncover physics behind neutrino mass and mixing are described. Goals of future studies…
Neutrino oscillations present the only robust example of experimentally detected physics beyond the standard model. This review discusses the established and several hypothetical beyond standard models neutrino characteristics and their…
The Standard Model of Particle Physics has proven to be tremendously successful as the fundamental theory that describes the elementary particles that compose our Universe, as well as the interactions among them. Despite the countless…
Machine learning promises to deliver powerful new approaches to neutron scattering from magnetic materials. Large scale simulations provide the means to realise this with approaches including spin-wave, Landau Lifshitz, and Monte Carlo…
An overview of neutrino electromagnetic properties, which open a door to the new physics beyond the Standard Model, is given. The effects of neutrino electromagnetic interactions both in terrestrial experiments and in astrophysical…
Neutrino interaction uncertainties are a limiting factor in current and next-generation experiments probing the fundamental physics of neutrinos, a unique window on physics beyond the Standard Model. Neutrino-nucleon scattering amplitudes…
The fact that neutrinos have mass allows them to possess many other properties, like a magnetic dipole moment and a finite decay width. Theoretical expectations for these are, however, well beyond current experimental bounds, and the…
Applications of machine learning tools to problems of physical interest are often criticized for producing sensitivity at the expense of transparency. To address this concern, we explore a data planing procedure for identifying combinations…
As ultracold atom experiments become highly controlled and scalable quantum simulators, they require sophisticated control over high-dimensional parameter spaces and generate increasingly complex measurement data that need to be analyzed…
Neutrinos are the least known particle in the Standard Model of elementary particle physics. They play a crucial role in cosmology, governing the universe's evolution and shaping the large-scale structures we observe today. In this chapter,…
Machine learning (ML) is becoming an increasingly important component of cutting-edge physics research, but its computational requirements present significant challenges. In this white paper, we discuss the needs of the physics community…
An array of powerful neutrino-beam experiments will study the fundamental properties of neutrinos with unprecedented precision in the coming years. Along with their primary neutrino-physics motivations, there has been growing recognition…
Machine learning is poised as a very powerful tool that can drastically improve our ability to carry out scientific research. However, many issues need to be addressed before this becomes a reality. This article focuses on one particular…
Modern machine learning techniques, including deep learning, are rapidly being applied, adapted, and developed for high energy physics. Given the fast pace of this research, we have created a living review with the goal of providing a…
Machine learning algorithms have recently emerged as a tool to generate force fields which display accuracies approaching the ones of the ab-initio calculations they are trained on, but are much faster to compute. The enhanced computational…
A revolution in our understanding of the neutrino sector is underway, driven by observations that are interpreted in terms of changes in neutrino flavors as they propagate. Since neutrino oscillations occur only if neutrinos are massive,…
This article reviews our present knowledge of neutrino interactions with nucleons and discusses the interactions with nuclei, the target material of all presently running and planned long-baseline experiments. I emphasize descriptions of…
Neutrino oscillation experiments aim to measure the neutrino oscillation parameters with accuracy and achieve a complete understanding of neutrino physics. For determining the neutrino oscillation parameters, knowledge of neutrino energy is…