相关论文: Conjugate gradient methods in micromagnetics
As deep learning models and datasets rapidly scale up, network training is extremely time-consuming and resource-costly. Instead of training on the entire dataset, learning with a small synthetic dataset becomes an efficient solution.…
We study the worst-case convergence rates of the proximal gradient method for minimizing the sum of a smooth strongly convex function and a non-smooth convex function whose proximal operator is available. We establish the exact worst-case…
We first propose a decentralized proximal stochastic gradient tracking method (DProxSGT) for nonconvex stochastic composite problems, with data heterogeneously distributed on multiple workers in a decentralized connected network. To save…
Magnetic fields are ubiquitous in the interstellar medium but are notoriously difficult to study through observation. Making use of the advances in our understanding of MHD turbulence and turbulent reconnection, the Velocity Gradient…
In this paper we present a subgradient method with non-monotone line search for the minimization of convex functions with simple convex constraints. Different from the standard subgradient method with prefixed step sizes, the new method…
We present a conjugate gradient method for calculating the entanglement of formation of arbitrary mixed quantum states of any dimension and with any bipartite division of the Hilbert space. The development of the gradient used by the…
We present a dynamical model that successfully explains the observed time evolution of the magnetization in diluted magnetic semiconductor quantum wells after weak laser excitation. Based on the pseudo-fermion formalism and a second order…
Atomic comagnetometers are used in searches for anomalous spin-dependent interactions. Magnetic field gradients are one of the major sources of systematic errors in such experiments. Here we describe a comagnetometer based on the nuclear…
Field-induced magnetization jumps with similar characteristics are observed at low temperature for the intermetallic germanide Gd5Ge4and the mixed-valent manganite Pr0.6Ca0.4Mn0.96Ga0.04O3. We report that the field location -and even the…
The performance of permanent magnets is intricately tied to their magnetic hysteresis loop. In this study, we investigate the heavy-fermion ferromagnet CeAgSb$_2$ through magnetization measurements under uniaxial stress. We observe a 2400 %…
Nonlinear conjugate gradients are among the most popular techniques for solving continuous optimization problems. Although these schemes have long been studied from a global convergence standpoint, their worst-case complexity properties…
The stripe state in the lowest Landau level is studied by the density matrix renormalization group (DMRG) method. The ground state energy and pair correlation functions are systematically calculated for various pseudopotentials in the…
The magnetization steps of quintet clusters, consisting of five identical magnetic ions coupled by isotropic nearest neighbors antiferromagnetic exchange interaction in the hcp lattice, have been investigated. In that model, called the…
A silicon micromechanical torsional oscillator is used to measure the hysteresis loops of two manganite La_0.67Ca_0.33MnO_3 nanotubes at different temperatures, applying an external field along its main axes. These structures are composed…
The ground state of 2D electrons in high magnetic field is studied by the density matrix renormalization group method. The ground state energy, excitation gap, and pair correlation functions are systematically calculated at various fillings…
We use a machine learning approach to identify the importance of microstructure characteristics in causing magnetization reversal in ideally structured large-grained Nd$_2$Fe$_{14}$B permanent magnets. The embedded Stoner-Wohlfarth method…
A recently proposed linear-scaling scheme for density-functional pseudopotential calculations is described in detail. The method is based on a formulation of density functional theory in which the ground state energy is determined by…
Identifying and characterizing systems with coupled and competing interactions is central to the development of physical models that can accurately describe and predict emergent behavior in condensed matter systems. This work demonstrates…
Distributed optimization increasingly plays a central role in economical and sustainable operation of cyber-physical systems. Nevertheless, the complete potential of the technology has not yet been fully exploited in practice due to…
Quasi-static hysteresis loops of spherical and spheroidal magnetite nanoparticles with semi-axes ratio a/b = 1.5 and 2.0 with different types of combined magnetic anisotropy are calculated using numerical simulation. For particles of each…