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A new methodology is developed to integrate numerically the equations of motion for classical many-body systems in molecular dynamics simulations. Its distinguishable feature is the possibility to preserve, independently on the size of the…

Statistical Mechanics · Physics 2009-10-31 I. P. Omelyan , I. M. Mryglod , R. Folk

Spin wave propagation and dynamic control are essential for reconfigurable magnonic and spintronic devices. Here, tunable mode coupling and band hybridisation are demonstrated in a nanopatterned bicomponent magnonic crystal consisting of a…

Mesoscale and Nanoscale Physics · Physics 2026-05-22 Nikhil Kumar

Optimal control of nanomagnets has become an urgent problem for the field of spintronics as technological tools approach thermodynamically determined limits of efficiency. In complex, fluctuating systems, like nanomagnetic bits, finding…

Statistical Mechanics · Physics 2017-02-01 Grant M. Rotskoff , Gavin E. Crooks , Eric Vanden-Eijnden

We study the linearized Vlasov equations and the linearized Vlasov-Fokker-Planck equations in the weakly collisional limit in a uniform magnetic field. In both cases, we consider periodic confinement and Maxwellian (or close to Maxwellian)…

Analysis of PDEs · Mathematics 2020-01-08 Jacob Bedrossian , Fei Wang

In this work, we consider the construction of efficient surrogates for the stochastic version of the Landau-Lifshitz-Gilbert (LLG) equation using model order reduction techniques, in particular, the Reduced Basis (RB) method. The Stochastic…

Numerical Analysis · Mathematics 2025-10-01 Andrea Scaglioni , Michael Feischl , Fernando Henríquez

Understanding the nonlinear dynamics of magnetic vortices in spin-torque vortex oscillators (STVOs) is essential for their application in neuromorphic computing. Conventional modeling approaches either rely on the standard Thiele equation,…

Mesoscale and Nanoscale Physics · Physics 2025-10-20 Colin Ducarme , Simon De Wergifosse , Flavio Abreu Araujo

We study the switching-process of the magnetization in a ferromagnetic-normal-metal multilayer system by a spin polarized electrical current via the spin transfer torque. We use a spin drift-diffusion equation (SDDE) and the…

Mesoscale and Nanoscale Physics · Physics 2013-01-16 M. Wenin , A. Windisch , W. Poetz

Galactic systems are inherently multiphase, and understanding the roles and interactions of the various phases is key towards a more complete picture of galaxy formation and evolution. For instance, these interactions play a pivotal role in…

Astrophysics of Galaxies · Physics 2025-02-07 Brent Tan

Unsteady nonlinear magnetization dynamics are studied in an easy-plane ferromagnetic channel subject to spin injection at one edge. The model Landau-Lifshitz equation is known to support steady-state solutions, termed dissipative exchange…

Mesoscale and Nanoscale Physics · Physics 2022-02-22 Mingyu Hu , Ezio Iacocca , Mark Hoefer

In this paper we consider unconditionally energy stable numerical schemes for the nonstationary 3D magneto-micropolar equations that describes the microstructure of rigid microelements in electrically conducting fluid flow under some…

Numerical Analysis · Mathematics 2024-03-19 Hailong Qiu

We propose an all spin state element to enable all spin state machines using spin currents and nanomagnets. We demonstrate via numerical simulations the operation of a state element a critical building block for synchronous, sequential…

Mesoscale and Nanoscale Physics · Physics 2015-06-11 Sasikanth Manipatruni , Dmitri E. Nikonov , Ian A. Young

Tailoring spin coupling to electric fields is central to spintronics and spin-based quantum information processing. We present an optimal micromagnet design that produces appropriate stray magnetic fields to mediate fast electrical spin…

This paper proposes a decoupled numerical scheme of the time-dependent Ginzburg--Landau equations under the temporal gauge. For the magnetic potential and the order parameter, the discrete scheme adopts the second type Ned${\rm…

Numerical Analysis · Mathematics 2023-07-26 Limin Ma , Zhonghua Qiao

Many applications in computational physics involve approximating problems with microstructure, characterized by multiple spatial scales in their data. However, these numerical solutions are often computationally expensive due to the need to…

Numerical Analysis · Mathematics 2023-09-15 Piermario Vitullo , Alessio Colombo , Nicola Rares Franco , Andrea Manzoni , Paolo Zunino

A phase diagram of the magnetization dynamics is studied by numerically solving the Landau-Lifshitz-Gilbert (LLG) equation in a spin torque oscillator consisting of asymmetric two free layers that are magnetized in in-plane direction. We…

Mesoscale and Nanoscale Physics · Physics 2019-04-19 Tomohiro Taniguchi

We consider the general Landau-Lifshitz-Gilbert theory underlying the magnetization dynamics of a macrospin magnet subject to spin-torque effects and thermal fluctuations. Thermally activated dynamical properties are analyzed by averaging…

Mesoscale and Nanoscale Physics · Physics 2013-10-07 Daniele Pinna , Andrew D. Kent , Daniel L. Stein

We present our open-source Python module Commics for the study of the magnetization dynamics in ferromagnetic materials via micromagnetic simulations. It implements state-of-the-art unconditionally convergent finite element methods for the…

Magnetic force microscopy and scanning tunneling microscopy data could be used to test computer numerical models of magnetism. The elaborated numerical model of a face-centered lattice Ising spins is based on pixel distribution in the image…

Computational Physics · Physics 2015-12-07 Vitalii Kapitan , Alexey Peretyatko , Konstantin Nefedev

Non-damped oscillations of the magnetization vector of a ferromagnetic system subject to a spin polarized current and an external magnetic field are studied theoretically by solving the Landau-Lifshitz-Gilbert equation. It is shown that the…

Materials Science · Physics 2007-05-23 P. M. Gorley , P. P. Horley , V. K. Dugaev , J. Barnas , V. R. Vieira

Classical neural ordinary differential equations (ODEs) are powerful tools for approximating the log-density functions in high-dimensional spaces along trajectories, where neural networks parameterize the velocity fields. This paper…

Optimization and Control · Mathematics 2025-01-30 Mo Zhou , Stanley Osher , Wuchen Li
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