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This important book presents the proceedings of the conference ?Neutrinos and Implications for Physics Beyond the Standard Model?, put on by the Yang Institute for Theoretical Physics, State University of New York at Stony Brook.The observation of neutrino masses and lepton mixing constitutes the first confirmed evidence for physics beyond the Standard Model. This evidence includes the measured deficiency of charged current reactions induced by solar neutrinos and the anomalous zenith angle distribution of atmospheric neutrinos. A profound question now facing theorists is: What do these observations imply for new physics? At the conference, members of the major experiments gave an update on ...
This volume outlines the status of fundamental physics at the threshold of the 21st century. Some of the world's leading theorists and experimentalists discuss ongoing research on the following topics: M Theory, Superstring Theory, Supersymmetry and Supergravity, Quantum Gravity, Dark Matter in the Universe, Gravitational Radiation, Proton Decay, Higgs Physics, Cosmology, Bose-Einstein Condensation.
Contains many discussions on phenomenology and theories about neutrino mass and oscillations.
This thesis describes one of the most precise experimental tests of Lorentz symmetry in electrodynamics by light-speed anisotropy measurement with an asymmetric optical ring cavity. The author aims to answer the fundamental, hypothetical debate on Lorentz symmetry in the Universe. He concludes that the symmetry is protected within an error of 10-15, which means providing one of the most stringent upper limits on the violation of the Lorentz symmetry in the framework of the Standard Model Extension. It introduces the following three keys which play an important role in achieving high-precision measurement: (1) a high-index element (silicon) interpolated into part of the light paths in the opt...
This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.
This book presents topics of major interest to the high energy physics community, as well as recent research results.
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