Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Spin–Spin Coupling Constant: Overview

Spin–Spin Coupling Constant: Overview

In bromoethane, the three methyl protons are coupled to the two methylene protons that are three bonds away. In accordance with the n+1 rule, the signal from the methyl protons is split into three peaks with 1:2:1 relative intensities. The methylene protons appear as a quartet, with the relative intensities of 1:3:3:1.
Qualitatively, any spin plus-half nucleus polarizes the spins of its electrons to the minus-half state. Consequently, the paired electron in the hydrogen–carbon bond must have a...

Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)

Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)

Two NMR-active nuclei bonded to a central atom can be involved in geminal or two-bond coupling. Geminal coupling is commonly seen between diastereotopic protons in chiral molecules and unsymmetrical alkenes, among others.
The central atom need not be NMR-active because its electrons are affected by the electron polarization of the spin-active atoms. However, spin information is transmitted less effectively than in one-bond coupling, and 2J values are usually weaker than 1J values. The energy of...

Atomic Nuclei: Types of Nuclear Relaxation

Atomic Nuclei: Types of Nuclear Relaxation

Nuclear relaxation restores the equilibrium population imbalance and can occur via spin–lattice or spin–spin mechanisms, which are first-order exponential decay processes.
In spin–lattice or longitudinal relaxation, the excited spins exchange energy with the surrounding lattice as they return to the lower energy level. Among several mechanisms that contribute to spin–lattice relaxation, magnetic dipolar interactions are significant. Here, the excited nucleus transfers energy to a nearby...

Spin–Spin Coupling: One-Bond Coupling

Spin–Spin Coupling: One-Bond Coupling

Coupling interactions are strongest between NMR-active nuclei bonded to each other, where spin information can be transmitted directly through the pair of bonding electrons. While nuclei polarize their electrons to the opposite spins, the bonding electron pair has opposite spins. Configurations with antiparallel nuclear spins are expected to be lower in energy. When coupling makes antiparallel states more favorable, J is considered to have a positive value. The one-bond coupling constant, 1J,...

The Pauli Exclusion Principle

The Pauli Exclusion Principle

The arrangement of electrons in the orbitals of an atom is called its electron configuration. We describe an electron configuration with a symbol that contains three pieces of information:

Atomic Nuclei: Nuclear Spin State Population Distribution

Atomic Nuclei: Nuclear Spin State Population Distribution

Near absolute zero temperatures, in the presence of a magnetic field, the majority of nuclei prefer the lower energy spin-up state to the higher energy spin-down state. As temperatures increase, the energy from thermal collisions distributes the spins more equally between the two states. The Boltzmann distribution equation gives the ratio of the number of spins predicted in the spin −½ (N−) and spin +½ (N+) states.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A feedforward unitary equivariant neural network.

Neural networks : the official journal of the International Neural Network Society·2023

Same author

A machine-learned spin-lattice potential for dynamic simulations of defective magnetic iron.

Scientific reports·2022

Same author

Parallel propagating electromagnetic waves in magnetized quantum electron plasmas with finite temperature.

Physical review. E·2020

Same author

Quantum de-trapping and transport of heavy defects in tungsten.

Nature materials·2020

Same author

Quantum statistical effects in the mass transport of interstitial solutes in a crystalline solid.

Physical review. E·2018

Same author

3D lattice distortions and defect structures in ion-implanted nano-crystals.

Scientific reports·2017

Same journal

Tension on dsDNA bound to ssDNA-RecA filaments may play an important role in driving efficient and accurate homology recognition and strand exchange.

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

Same journal

Publisher's Note: Amplitude-phase coupling drives chimera states in globally coupled laser networks [Phys. Rev. E 91, 040901(R) (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

Same journal

Erratum: Shapes of sedimenting soft elastic capsules in a viscous fluid [Phys. Rev. E 92, 033003 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

Same journal

Erratum: Attenuation of excitation decay rate due to collective effect [Phys. Rev. E 90, 022142 (2014)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

Same journal

Publisher's Note: Role of connectivity and fluctuations in the nucleation of calcium waves in cardiac cells [Phys. Rev. E 92, 052715 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

Same journal

Publisher's Note: Lattice Boltzmann approach for complex nonequilibrium flows [Phys. Rev. E 92, 043308 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 22, 2026

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Published on: August 22, 2025

Parallel algorithm for spin and spin-lattice dynamics simulations.

Pui-Wai Ma¹, C H Woo

¹Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|June 13, 2009

Summary

This summary is machine-generated.

A new parallel algorithm enhances spin dynamics simulations by using second-order Suzuki-Trotter decomposition (STD). This method ensures numerical accuracy and stability over millions of time steps, improving computational efficiency.

More Related Videos

New Features in Visual Dynamics 3.0

New Features in Visual Dynamics 3.0

Published on: August 9, 2024

Related Experiment Videos

Last Updated: Jun 22, 2026

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Published on: August 22, 2025

New Features in Visual Dynamics 3.0

New Features in Visual Dynamics 3.0

Published on: August 9, 2024

Area of Science:

Computational physics
Materials science

Background:

Numerical integration of coupled equations of motion presents challenges with accumulating errors over extended time steps.
Accurate simulations of spin dynamics and spin-lattice dynamics are crucial for understanding magnetic materials.

Purpose of the Study:

To develop and validate a parallel algorithm for spin dynamics and spin-lattice dynamics simulations.
To address numerical errors and improve the stability and accuracy of long-time simulations.

Main Methods:

Implementation of a parallel algorithm based on the second-order Suzuki-Trotter decomposition (STD).
Testing the algorithm on simulations involving up to a million spins for both spin dynamics and spin-lattice dynamics.
Mathematical analysis of the symplecticity of the decomposed evolution operators.

Main Results:

The algorithm demonstrates good stability and numerical accuracy over millions of time steps (approx. 1 ns).
The STD-based scheme effectively avoids numerical energy dissipation, mitigating trajectory and machine errors.
Achieved a six to seven times speedup with eight threads, showing linear scalability with system size.

Conclusions:

The proposed parallel algorithm offers a robust and efficient solution for advanced spin dynamics simulations.
The method ensures high numerical fidelity, essential for exploring complex magnetic phenomena.
The parallel implementation significantly enhances computational performance for large-scale spin system modeling.