English
Related papers

Related papers: Effective phase diffusion for spin phase evolution…

200 papers

High diffusion-sensitizing magnetic field gradients have been more and more often applied nowadays to achieve a better characterization of the microstructure. As the resulting spin-echo signal significantly deviates from the conventional…

Statistical Mechanics · Physics 2021-10-14 N. Moutal , D. S. Grebenkov

It is well-known that many diffusion equations can be recast as Wasserstein gradient flows. Moreover, in recent years, by modifying the Wasserstein distance appropriately, this technique has been transferred to further evolution equations…

Probability · Mathematics 2020-10-15 Kaveh Bashiri , Anton Bovier

Magnetic response of the spin-$1/2$ cylindrical nanowire to the propagating magnetic field wave has been investigated by means of Monte Carlo simulation method based on Metropolis algorithm. The obtained microscopic spin configurations…

Statistical Mechanics · Physics 2017-06-14 Erol Vatansever

Transport properties in fluids and confined systems play a central role across a wide range of natural and technological contexts, from geology and environmental sciences to biology, energy storage, and membrane-based separation processes.…

Nonlinear spin dynamics are essential in exploring nonequilibrium quantum phenomena and have broad applications in precision measurement. Among these systems, the combination of a bias magnetic field and feedback mechanisms can induce…

Quantum Physics · Physics 2024-10-29 Tishuo Wang , Zhihuang Luo , Shizhong Zhang , Zhenhua Yu

In this Letter we show how the nonlinear evolution of a resonant triad depends on the special combination of the modes' phases chosen according to the resonance conditions. This phase combination is called dynamical phase. Its evolution is…

Exactly Solvable and Integrable Systems · Physics 2009-11-13 Miguel D. Bustamante , Elena Kartashova

We develop methods for investigating protein drift-diffusion dynamics in heterogeneous cell membranes and the roles played by geometry, diffusion, chemical kinetics, and phase separation. Our hybrid stochastic numerical methods combine…

Biological Physics · Physics 2023-02-28 Patrick D. Tran , Thomas A. Blanpied , Paul J. Atzberger

A particle with internal unobserved states diffusing in a force field will generally display effective advection-diffusion. The drift velocity is proportional to the mobility averaged over the internal states, or effective mobility, while…

Statistical Mechanics · Physics 2017-10-13 Erik Aurell , Stefano Bo

Anomalous diffusion exists widely in polymer and biological systems. Pulsed field gradient (PFG) techniques have been increasingly used to study anomalous diffusion in NMR and MRI. However, the interpretation of PFG anomalous diffusion is…

Chemical Physics · Physics 2016-11-22 Guoxing Lin

We propose a novel learning framework using neural mean-field (NMF) dynamics for inference and estimation problems on heterogeneous diffusion networks. Our new framework leverages the Mori-Zwanzig formalism to obtain an exact evolution…

Machine Learning · Computer Science 2021-06-07 Shushan He , Hongyuan Zha , Xiaojing Ye

In the present work fournontrivial stages of electrokinetic instability are identified by direct numerical simulation (DNS) of the full Nernst-Planck-Poisson-Stokes (NPPS) system: i) The stage of the influence of the initial conditions…

Fluid Dynamics · Physics 2015-03-19 E. A. Demekhin , V. S. Shelistov , S. V. Polyanskikh

Propagation of energetic particles across the mean field direction in turbulent magnetic fields is often described as spatial diffusion. Recently, it has been suggested that initially the particles propagate systematically along meandering…

Space Physics · Physics 2017-06-22 T. Laitinen , S. Dalla , D. Marriott

The dielectric permeability tensor for spin polarized plasmas derived in terms of the spin-1/2 quantum kinetic model in six-dimensional phase space in Part I of this work is applied for study of spectra of high-frequency transverse and…

Plasma Physics · Physics 2017-03-08 Pavel A. Andreev

We provide a microscopic theory for the Doppler velocimetry of spin propagation in the presence of spatial inhomogeneity, driving electric field and the spin orbit coupling in semiconductor quantum wells in a wide range of temperature…

Mesoscale and Nanoscale Physics · Physics 2012-11-12 M. Q. Weng , M. W. Wu

Using a macroscopic analysis, we show that time-dependent noncollinear spin transport possesses a wavelike character. This leads to modifications of pure spin-diffusion dynamics and allows one to extract a finite spin-signal propagation…

Materials Science · Physics 2013-05-29 Yao-Hui Zhu , Burkard Hillebrands , Hans Christian Schneider

By studying the time and spatial evolution of a pulse of the spin polarization in $n$-type semiconductor quantum wells, we highlight the importance of the off-diagonal spin coherence in spin diffusion and transport. Spin oscillations and…

Condensed Matter · Physics 2007-05-23 M. Q. Weng , M. W. Wu , Q. W. Shi

A fourth-order and a second-order nonlinear diffusion models in spectral space are proposed to describe gravitational wave turbulence in the approximation of strongly local interactions. We show analytically that the model equations satisfy…

General Relativity and Quantum Cosmology · Physics 2019-03-27 Sébastien Galtier , Sergey V. Nazarenko , Éric Buchlin , Simon Thalabard

In semiconductor spintronic devices, the semiconductor is usually lightly doped and nondegenerate, and moderate electric fields can dominate the carrier motion. We recently derived a drift-diffusion equation for spin polarization in the…

Materials Science · Physics 2009-11-07 Z. G. Yu , M. E. Flatte

This paper analyzes theoretically the signal propagation in spin transport by modulating the current passing through magnetic multilayers. Using a macroscopic description of spin transport based on the dynamical Boltzmann equation, we show…

Other Condensed Matter · Physics 2009-11-13 Yao-Hui Zhu , Burkard Hillebrands , Hans Christian Schneider

We use a Convolutional Recurrent Neural Network approach to learn morphological evolution driven by surface diffusion. To this aim we first produce a training set using phase field simulations. Intentionally, we insert in such a set only…

Computational Physics · Physics 2024-05-07 Daniele Lanzoni , Marco Albani , Roberto Bergamaschini , Francesco Montalenti