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Variance reduction is a crucial tool for improving the slow convergence of stochastic gradient descent. Only a few variance-reduced methods, however, have yet been shown to directly benefit from Nesterov's acceleration techniques to match…
Federated learning is highly valued due to its high-performance computing in distributed environments while safeguarding data privacy. To address resource heterogeneity, researchers have proposed a semi-asynchronous federated learning…
Recently observed scaling in the random-anisotropy model of amorphous or sintered ferromagnets is derived by an alternative method and extended for studying the dynamical properties in terms of the Landau-Lifshitz equations for spin blocks.…
SGD (Stochastic Gradient Descent) is a popular algorithm for large scale optimization problems due to its low iterative cost. However, SGD can not achieve linear convergence rate as FGD (Full Gradient Descent) because of the inherent…
This article introduces a new physics-based method for rigid point set alignment called Fast Gravitational Approach (FGA). In FGA, the source and target point sets are interpreted as rigid particle swarms with masses interacting in a…
Magnetic fields from the brain are tiny relative to ambient fields which therefore need to be suppressed. The common solution of passive shielding is expensive, bulky and insufficiently effective, thus motivating research into the…
This paper describes performance of a voltage controlled phase shifter designed for a high average power and a high figure of merit. The device is a reflection-type, resonant phase shifter that utilizes ferroelectric capacitors and…
Edge computing allows artificial intelligence and machine learning models to be deployed on edge devices, where they can learn from local data and collaborate to form a global model. Federated learning (FL) is a distributed machine learning…
Generative recommendation (GR) has emerged as a promising paradigm that replaces fragmented, scenario-specific architectures with unified Transformer-based models, exhibiting scaling-law behavior where recommendation quality improves…
The classical convex feasibility problem in a finite dimensional Euclidean space is studied in the present paper. We are interested in two cases. First, we assume to know how to compute an exact project onto one of the sets involved and the…
The discovery of altermagnetism offers new opportunities for exploring novel quantum states and developing spintronic devices for enabling momentum dependent spin splitting in compensated systems, while zero net magnetization limit its…
Radio Frequency Quadrupole (RFQ) accelerators often need to face the challenges of space charge effects from high beam currents. This study investigated how to reach RFQ beam dynamics designs with not only high beam transmission and short…
Singlet fission (SF) is an electronic transition that in the last decade has been under the spotlight for its applications in optoelectronics, from photovoltaics to spintronics. Despite considerable experimental and theoretical…
This paper is a summary report of the ICFA Beam Dynamics Workshop 'Accelerators for a Higgs Factory: Linear vs. Circular' (HF2012). It discusses four types of accelerators as possible candidates for a Higgs factory: linear e+e- colliders,…
The generic vector memory based accelerator is considered which supports DIT and DIF FFT with fixed datapath. The regular mixed-radix factorization of the DFT matrix coherent with the accelerator architecture is proposed and the correction…
We introduce a vector atomic magnetometer that employs a fast-rotating magnetic field applied to a pulsed $^{87}$Rb scalar atomic magnetometer. This approach enables simultaneous measurements of the total magnetic field and its two polar…
This paper proposes an extra gradient Anderson-accelerated algorithm for solving pseudomonotone variational inequalities, which uses the extra gradient scheme with line search to guarantee the global convergence and Anderson acceleration to…
Surface acceleration of fast electrons in intense laser-plasma interaction is improved by using sub-wavelength grating targets. The fast electron beam emitted along the target surface was enhanced by more than three times relative to that…
Structure factor twist averaging (sfTA) is a newer method that has been shown to reproduce twist-averaged (TA) CCSD energies for bulk systems at a low computational cost. In this work, we extend this method for the treatment of…
This paper presents two inexact composite gradient methods, one inner accelerated and another doubly accelerated, for solving a class of nonconvex spectral composite optimization problems. More specifically, the objective function for these…