Results 131 to 140 of about 376,317 (337)

On the Classical Interpretation of Schwinger Boson Representation for the Quantized Rotator [PDF]

, 1978
Hiroshi Ichihashi, M. Yamamura
openalex   +1 more source

RRAM Variability Harvesting for CIM‐Integrated TRNG

Advanced Electronic Materials, EarlyView.
This work demonstrates a compute‐in‐memory‐compatible true random number generator that harvests intrinsic cycle‐to‐cycle variability from a 1T1R RRAM array. Parallel entropy extraction enables high‐throughput bit generation without dedicated circuits. This approach achieves NIST‐compliant randomness and low per‐bit energy, offering a scalable hardware
Ankit Bende, Gokulnath Rajendran, Regina Dittmann, Anupam Chattopadhyay, Vikas Rana   +4 more
wiley   +1 more source

SpQuant-SNN: ultra-low precision membrane potential with sparse activations unlock the potential of on-device spiking neural networks applications

Frontiers in Neuroscience
Spiking neural networks (SNNs) have received increasing attention due to their high biological plausibility and energy efficiency. The binary spike-based information propagation enables efficient sparse computation in event-based and static computer ...
Ahmed Hasssan, Jian Meng, Anupreetham Anupreetham, Jae-sun Seo   +3 more
doaj   +1 more source

Erratum to: QED in Krein Space Quantization [PDF]

, 2012
Ali Asghar Zarei, B. Forghan, M. V. Takook   +2 more
openalex   +1 more source

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

Advanced 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

Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization [PDF]

, 2018
Jiaxiang Wu, Weidong Huang, Junzhou Huang, Tong Zhang   +3 more
openalex   +1 more source

XpulpNN: Enabling Energy Efficient and Flexible Inference of Quantized\n Neural Network on RISC-V based IoT End Nodes [PDF]

, 2020
Angelo Garofalo, Giuseppe Tagliavini, Francesco Conti, Luca Benini, Davide Rossi   +4 more
openalex   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Quantization of classical singular solutions in Yang-Mills theory [PDF]

, 1999
Vladimir Dzhunushaliev, Douglas Singleton   +1 more
openalex   +1 more source

Recent Advances in Programmable Metasurfaces and Meta‐Devices

Advanced Electronic Materials, EarlyView.
Programmable metasurfaces enable various novel functionalities by dynamically tuning electromagnetic wavefronts. This article provides a comprehensive review of recent advances in microwave and terahertz programmable metasurfaces, covering electrical, thermal, optical, and mechanical control mechanisms.
Linda Shao, Chong He, Nan Wang, Liming Si, Weiren Zhu   +4 more
wiley   +1 more source