Results 11 to 20 of about 370,968 (321)
, 2013 Radio-frequency linear accelerators are used as injectors for synchrotrons and as stand-alone accelerators for the production of intense particle beams, thanks to their ability to accelerate high beam currents at high repetition rates.
Vretenar, Maurizio
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Gravitomagnetic Accelerators [PDF]
Physics Letters A, 2010 We study a simple class of time-dependent rotating Ricci-flat cylindrically symmetric spacetime manifolds whose geodesics admit gravitomagnetic jets. The helical paths of free test particles in these jets up and down parallel to the rotation axis are ...
B. Mashhoon +34 more
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AIP Conference Proceedings, 2003 I describe the future accelerator facilities that are currently foreseen for electroweak scale physics, neutrino physics, and nuclear structure. I will explore the physics justification for these machines, and suggest how the case for future accelerators
Womersley, John
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Acceleration modules in linear induction accelerators [PDF]
Chinese Physics C, 2014 Linear Induction Accelerator (LIA) is a unique type of accelerator, which is capable to accelerate kilo-Ampere beam current to tens of MeV. The LIA acceleration modules, filled with ferrite or ferromagnetic toroid cores, can be conveniently stacked to obtain high energy. During the evolution of LIA, several models for the LIA acceleration module and the
Wang, Shaoheng, Deng, Jianjun
openaire +2 more sources
Computing Graph Neural Networks: A Survey from Algorithms to Accelerators [PDF]
ACM Computing Surveys, 2020 Graph Neural Networks (GNNs) have exploded onto the machine learning scene in recent years owing to their capability to model and learn from graph-structured data.
S. Abadal +4 more
semanticscholar +1 more source
Odd entanglement entropy and logarithmic negativity for thermofield double states
Journal of High Energy Physics, 2021 We investigate the time evolution of odd entanglement entropy (OEE) and logarithmic negativity (LN) for the thermofield double (TFD) states in free scalar quantum field theories using the covariance matrix approach.
Mostafa Ghasemi +2 more
doaj +1 more source
International Symposium on Computer Architecture, 2022 Hardware specialization is a promising trend to sustain performance growth. Spatial hardware accelerators that employ specialized and hierarchical computation and memory resources have recently shown high performance gains for tensor applications such as
Size Zheng +9 more
semanticscholar +1 more source
Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications [PDF]
IEEE Transactions on Biomedical Circuits and Systems, 2020 The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) algorithms to healthcare and biomedical applications at the edge.
M. Azghadi +6 more
semanticscholar +1 more source
SoK: Fully Homomorphic Encryption Accelerators [PDF]
ACM Computing Surveys, 2022 Fully Homomorphic Encryption (FHE) is a key technology enabling privacy-preserving computing. However, the fundamental challenge of FHE is its inefficiency, due primarily to the underlying polynomial computations with high computation complexity and ...
Junxue Zhang +5 more
semanticscholar +1 more source
Survey of Machine Learning Accelerators [PDF]
IEEE Conference on High Performance Extreme Computing, 2020 New machine learning accelerators are being announced and released each month for a variety of applications from speech recognition, video object detection, assisted driving, and many data center applications.
A. Reuther +5 more
semanticscholar +1 more source