Related papers: Fixed field alternating gradient
This work proposes a novel adaptive background compensation scheme for frequency interleaved digital-to-analog converters (FI-DACs). The technique is applicable to high speed digital transceivers such as those used in coherent optical…
In view of the large amount of calculation and long calculation time of convolutional neural network (CNN), this paper proposes a convolutional neural network hardware accelerator based on field programmable logic gate array (FPGA). First,…
Federated averaging (FedAvg) is a popular federated learning (FL) technique that updates the global model by averaging local models and then transmits the updated global model to devices for their local model update. One main limitation of…
In a plasma wakefield accelerator driven by a train of short particle bunches, it is possible to locally increase the acceleration rate by introducing a small negative gradient of the plasma density. A regime is possible in which the…
It is well known that the tuning of a long radio-frequency quadrupole accelerator is demanding. This study investigated how to realize efficient long RFQ accelerators with multiple shorter and independent cavities. From the RF point of…
A high-intensity laser beam propagating through a dense plasma drives a strong current that robustly sustains a strong quasi-static Mega Tesla-level azimuthal magnetic field. The transverse laser field efficiently accelerates electrons in…
Riemannian accelerated gradient methods have been well studied for smooth optimization, typically treating geodesically convex and geodesically strongly convex cases separately. However, their extension to nonsmooth problems on manifolds…
A lattice of single aperture superconducting variable field bending magnets is proposed as a cheap and practical way to recirculate the beams in recirculating linear accelerators. It is shown that the VFBM's can be configured to provide…
Domain-specialized FPGAs have delivered unprecedented performance for low-latency inference across scientific and industrial workloads, yet nearly all existing accelerators assume static models trained offline, relegating learning and…
Due to recent advances in digital technologies, and availability of credible data, an area of artificial intelligence, deep learning, has emerged, and has demonstrated its ability and effectiveness in solving complex learning problems not…
In this Letter we report on the experimental generation of high energy (10 GeV), ultra-short (fs-duration), ultra-high current (0.1 MA), petawatt peak power electron beams in a particle accelerator. These extreme beams enable the…
The Fast Fourier Transform is extended to functions on finite graphs whose edges are identified with intervals of finite length. Spectral and pseudospectral methods are developed to solve a wide variety of time dependent partial…
Laser powered dielectric structures achieve high-gradient particle acceleration by taking advantage of modern laser technology capable of producing electric fields in excess of 10GV/m. These fields can drive the bulk dielectric beyond its…
Offloading compute intensive nested loops to execute on FPGA accelerators have been demonstrated by numerous researchers as an effective performance enhancement technique across numerous application domains. To construct such accelerators…
This recounting of the history of the last three-and-a-half decades of advanced accelerator concepts is offered from a decidedly parochial point of view -- that of the career of the author, Prof. James Rosenzweig of the UCLA Dept. of…
In recent years, deep learning has become more and more mature, and as a commonly used algorithm in deep learning, convolutional neural networks have been widely used in various visual tasks. In the past, research based on deep learning…
Deformable convolutional networks have demonstrated outstanding performance in object recognition tasks with an effective feature extraction. Unlike standard convolution, the deformable convolution decides the receptive field size using…
In this paper, the acceleration of algorithms using a design of a field programmable gate array (FPGA) as a prototype of a static dataflow architecture is discussed. The static dataflow architecture using operators interconnected by…
An upgrade of the Jefferson Lab IR FEL is now under construction. It will provide 10 kW output light power in a wavelength range of 2-10 microns. The FEL will be driven by a modest-sized 80-210 MeV, 10 mA energy-recovering superconducting…
Domain adaptive object detection (DAOD) aims to improve the generalization ability of detectors when the training and test data are from different domains. Considering the significant domain gap, some typical methods, e.g., CycleGAN-based…