Hasil untuk "Physics"

J. Jaeckel, A. Ringwald

Most embeddings of the Standard Model into a more unified theory, in particular those based on supergravity or superstrings, predict the existence of a hidden sector of particles that have only very weak interactions with visible-sector Standard Model particles. Some of these exotic particle candidates [for instance, axions, axion-like particles, and hidden U(1) gauge bosons] may be very light, with masses in the subelectronvolt range, and may have very weak interactions with photons. Correspondingly, these very weakly interacting subelectronvolt particles (WISPs) may lead to observable effects in experiments (as well as in astrophysical and cosmological observations) searching for light shining through a wall, for changes in laser polarization, for nonlinear processes in large electromagnetic fields, and for deviations from Coulomb's law. We present the physics case and a status report of this emerging low-energy frontier of fundamental physics.

I. Hamley

K. Kampert

The study of high energy cosmic rays is a diversified field of observational and phenomenological physics addressing questions ranging from shock acceleration of charged particles in various astrophysical objects, via transport properties through galactic and extragalactic space, to questions of dark matter, and even to those of particle physics beyond the Standard Model including processes taking place in the earliest moments of our Universe. After decades of mostly independent evolution of nuclear, particle and high energy cosmic ray physics we find ourselves entering a symbiotic era of these fields of research. Some examples of interrelations will be given from the perspective of modern Particle-Astrophysics and new major experiments will briefly be sketched.

M. Reed, B. Simon

David P Landau, Kurt Binder

Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. The 5th edition contains extensive new material describing numerous powerful algorithms and methods that represent recent developments in the field. New topics such as active matter and machine learning are also introduced. Throughout, there are many applications, examples, recipes, case studies, and exercises to help the reader fully comprehend the material. This book is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.

D. E. Kerr

Enrique Cerda, Enrique Cerda, Lakshminarayanan Mahadevan

H. Sverdrup, Martin W. Johnson, R. H. Fleming

S. Zienau

J. Moll

L. C. Woods

N. Glendenning

E. Gadioli, P. Hodgson, E. Erba

J. Beeby

P. Langacker

The $\mathrm{U}{(1)}^{\ensuremath{'}}$ symmetry associated with a possible heavy ${Z}^{\ensuremath{'}}$ would have profound implications for particle physics and cosmology. The motivations for such particles in various extensions of the standard model, possible ranges for their masses and couplings, and classes of anomaly-free models are discussed. Present limits from electroweak and collider experiments are briefly surveyed, as are prospects for discovery and diagnostic study at future colliders. Implications of a ${Z}^{\ensuremath{'}}$ are discussed, including an extended Higgs sector, extended neutralino sector, and solution to the $\ensuremath{\mu}$ problem in supersymmetry; exotic fermions needed for anomaly cancellation; possible flavor changing neutral current effects; neutrino mass; possible ${Z}^{\ensuremath{'}}$ mediation of supersymmetry breaking; and cosmological implications for cold dark matter and electroweak baryogenesis.

G. Prettyman

Y. Shao

D. L. Turcotte, E. Moores, J. Rundle

R. Turolla, S. Zane, A. Watts

Magnetars are the strongest magnets in the present universe and the combination of extreme magnetic field, gravity and density makes them unique laboratories to probe current physical theories (from quantum electrodynamics to general relativity) in the strong field limit. Magnetars are observed as peculiar, burst–active x-ray pulsars, the anomalous x-ray pulsars (AXPs) and the soft gamma repeaters (SGRs); the latter emitted also three ‘giant flares’, extremely powerful events during which luminosities can reach up to 1047erg s−1 for about one second. The last five years have witnessed an explosion in magnetar research which has led, among other things, to the discovery of transient, or ‘outbursting’, and ‘low-field’ magnetars. Substantial progress has been made also on the theoretical side. Quite detailed models for explaining the magnetars’ persistent x-ray emission, the properties of the bursts, the flux evolution in transient sources have been developed and confronted with observations. New insight on neutron star asteroseismology has been gained through improved models of magnetar oscillations. The long-debated issue of magnetic field decay in neutron stars has been addressed, and its importance recognized in relation to the evolution of magnetars and to the links among magnetars and other families of isolated neutron stars. The aim of this paper is to present a comprehensive overview in which the observational results are discussed in the light of the most up-to-date theoretical models and their implications. This addresses not only the particular case of magnetar sources, but the more fundamental issue of how physics in strong magnetic fields can be constrained by the observations of these unique sources.

Santu Mondal, Sneha Ray, Aritra Acharyya et al.

This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regime. A comprehensive dataset, derived from self-consistent quantum drift-diffusion (SCQDD) simulations of GaN IMPATT structures designed for a wide frequency range from the microwave frequency bands, up to 5 THz, is used to train the ANN models. The models effectively capture the impact of variations in structural, doping, and biasing parameters on device performance. The proposed ANN approach significantly reduces computational time for predicting breakdown characteristics, power output, and conversion efficiency properties of IMPATT sources, achieving similar accuracy to traditional SCQDD simulations while requiring only 7.8&#x2013;20.1% of the computational time. Mean square errors are observed to be on the order of <inline-formula> <tex-math notation="LaTeX">$10^{-4}$ </tex-math></inline-formula>&#x2013;<inline-formula> <tex-math notation="LaTeX">$10^{-6}$ </tex-math></inline-formula>, demonstrating the models&#x2019; high accuracy. Experimental validation shows strong agreement in terms of breakdown voltage, power output, and efficiency, supporting the potential of machine learning to streamline the design and optimization of high-frequency semiconductor devices.