Results 101 to 110 of about 275,056 (272)

Superradiance and Broadband Emission Driving Fast Electron Dephasing in Open Quantum Systems

open access: yesAdvanced Science, EarlyView.
We uncover the physical origin of ultrafast electron dephasing in solid‐state high‐harmonic generation by simulating the Lindblad equation for the dissipative Hubbard model. Coexistence of Dicke superradiance and broadband emission is revealed, whose destructive interference shortens the effective scattering time and provides a unified picture of ...
Gimin Bae, Youngjae Kim, Jae Dong Lee
wiley   +1 more source

Ultra‐Wide‐Field Noninvasive Imaging Through Scattering Media Via Physics‐Guided Deep Learning

open access: yesAdvanced Science, EarlyView.
We propose a physics‐guided adaptive dual‐domain learning method for ultra‐wide‐field noninvasive imaging through scattering media, namely UNI‐Net. Our method not only reduces the requirement for real experimental data by an order of magnitude but also enables clear imaging of complex scenes with an ultra‐large field of view, which is 164 times the OME
Lintao Peng   +5 more
wiley   +1 more source

Conformal Reconfigurable Intelligent Surfaces: A Cylindrical Geometry Perspective

open access: yesAdvanced Electronic Materials, EarlyView.
Cylindrical reconfigurable intelligent surfaces are explored for low‐complexity beam steering using one‐bit meta‐atoms. A multi‐level modeling approach, including optimization‐based synthesis, demonstrates that even minimal hardware can support directive scattering.
Filippo Pepe   +4 more
wiley   +1 more source

Real time holography for higher spin theories

open access: yesJournal of High Energy Physics
Real time holography is studied in the context of the embedding space formalism. In the first part of this paper, we present matching conditions for on-shell integer spin fields when going from Euclidean to Lorentzian signature on AdS background.
Zezhuang Hao
doaj   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

open access: yesAdvanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Exceptional Antimodes in Multi‐Drive Cavity Magnonics

open access: yesAdvanced Electronic Materials, EarlyView.
Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith   +4 more
wiley   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

open access: yesAdvanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez   +10 more
wiley   +1 more source

R-algorithm for Solving Quadratic Programming Problems

open access: yesКібернетика та комп'ютерні технології
Quadratic programming problems have a wide range of practical applications in various fields of science and engineering, particularly in financial modeling and pattern recognition, which underscores the relevance of studying methods for their efficient ...
Petro Stetsyuk   +3 more
doaj   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

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