Related papers: A Review on Machine Learning for Neutrino Experime…
The present thesis aims to be an analysis of various aspects of neutrino phenomenology in two different scenarios. On the one hand, we address the study of non-standard neutrino interactions (NSI) in accelerator and reactor terrestrial…
Neutrinos, and primarily neutrino oscillations, have undoubtedly been one of the most exciting topics in the field of high-energy physics over the past few years. The existence of neutrino oscillations would require an extension of the…
Neutrinos are amongst the most abundant particles in the universe. The fact that they are massive particles proves that the Standard Model is an incomplete theory and needs to be extended. This thesis focuses on the study of neutrino…
Neutrinos are the Standard Model (SM) particles which we understand the least, often due to how weakly they interact with the other SM particles. Beyond this, very little is known about interactions among the neutrinos, i.e., their…
Measuring the unknown neutrino oscillation parameters is one of the main aims in neutrino physics today. The measurement of these parameters is severely affected by the presence of degeneracies in the parameter space. Various neutrino…
Machine learning (ML) is transforming all areas of science. The complex and time-consuming calculations in molecular simulations are particularly suitable for a machine learning revolution and have already been profoundly impacted by the…
I present a grand view of some of the main particle physics challenges from a neutrino perspective. After a brief review of the current status of neutrino physics, I illustrate the possible role neutrinos can play in the elucidation of…
Traditionally, collider experiments have been the primary tool used in searching for particle physics beyond the Standard Model. In this talk, I will discuss alternative approaches for exploring exotic physics scenarios using high energy…
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…
Neutrinos provide a compelling avenue to explore physics beyond the Standard Model. This proceeding is a brief summary of a plenary talk given at the 12th Neutrino Oscillation Workshop (NOW2024). We present a discussion on various topics on…
Collisions at high-energy particle colliders are a traditionally fruitful source of exotic particle discoveries. Finding these rare particles requires solving difficult signal-versus-background classification problems, hence machine…
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 section, to determine 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…
Searching for non-standard neutrino interactions, as a means for discovering physics beyond the Standard Model, has one of the key goals of dedicated neutrino experiments, current and future. We demonstrate here that much of the parameter…
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…
Machine learning (ML) is a rapidly growing area of research in the field of particle physics, with a vast array of applications at the CERN LHC. ML has changed the way particle physicists conduct searches and measurements as a versatile…
A thorough understanding of neutrino-nucleus interactions physics is crucial to achieving precision goals in broader neutrino physics programs. The complexity of nuclei comprising the detectors and limited understanding of their weak…
Neutrino oscillation parameters can be understood in a better way by building a more complete picture of neutrino interactions. This poses a series of important theoretical and experimental challenges because of the elusive nature of…
Machine Learning (ML) is one of the most exciting and dynamic areas of modern research and application. The purpose of this review is to provide an introduction to the core concepts and tools of machine learning in a manner easily…
In this review, we highlight recent developments in the application of machine learning for molecular modeling and simulation. After giving a brief overview of the foundations, components, and workflow of a typical supervised learning…