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相关概念视频

Spin–Spin Coupling Constant: Overview01:08

Spin–Spin Coupling Constant: Overview

1.4K
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...
1.4K
Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)01:20

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

1.6K
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...
1.6K
Spin–Spin Coupling: One-Bond Coupling01:17

Spin–Spin Coupling: One-Bond Coupling

1.4K
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,...
1.4K
Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)01:22

Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)

1.5K
Vicinal or three-bond coupling is commonly observed between protons attached to adjacent carbons. Here, nuclear spin information is primarily transferred via electron spin interactions between adjacent C‑H bond orbitals. This generally favors the antiparallel arrangement of spins, so 3J values are usually positive.
The extent of coupling depends on the C‑C bond length, the two H‑C‑C angles, any electron-withdrawing substituents, and the dihedral angle between the involved orbitals. The...
1.5K
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

1.1K
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the...
1.1K
Equilibrium Conditions for a Particle01:23

Equilibrium Conditions for a Particle

2.1K
When an object is in equilibrium, it is either at rest or moving with a constant velocity. There are two types of equilibrium: static and dynamic. Static equilibrium occurs when an object is at rest, while dynamic equilibrium occurs when an object is moving with a constant velocity. In both cases, there must be a balance of forces acting on the object.
To understand the concept of equilibrium, let us first consider the forces acting on an object. When different forces act on an object, they can...
2.1K

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Updated: Jan 14, 2026

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以温度为条件的深度生成框架,用于可扩展的Ising旋转配置合成,使用基于物理的约束条件.

Abhishek Kumar1, Partha Sarathi Bishnu1, Debabrata Deb2

  • 1Birla Institute of Technology, Mesra, Department of Computer Science and Engineering, Ranchi-835215, Jharkhand, India.

Physical review. E
|October 21, 2025
PubMed
概括

本研究介绍了一种深度学习方法,用于为2D Ising模型生成准确的旋转配置. 该方法有效地创建合成数据,这对于理解相位过渡和复杂的物理系统至关重要.

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科学领域:

  • 统计力学 统计力学
  • 计算物理 计算物理
  • 机器学习 机器学习

背景情况:

  • 2D Ising模型是统计力学的一个基本模型,用于理解磁力和相位过渡.
  • 生成精确的旋转配置是计算密集的,特别是在大型系统或临界点附近.
  • 深度生成模型为物理系统的高效和可扩展的模拟提供了潜力.

研究的目的:

  • 开发一种温度调节的深度生成方法,用于在2D Ising模型中高效地生成旋转配置.
  • 确保生成的配置的物理一致性和热力学准确性.
  • 提供一种可扩展的方法,用于创建合成数据,以进一步分析相位转换.

主要方法:

  • 采用了一个由旋转状态,温度和噪声决定的卷积发电机网络.
  • 基于物理学的约束 (磁化,能量,相关性) 被整合为辅助损失项.
  • 使用蒙特卡洛模拟来得出基线数据和训练约束.

主要成果:

  • 该模型生成了热力学准确的旋转配置,与各种格子大小 (L=16,32,64) 的蒙特卡洛基线密切匹配.
  • 平均绝对误差在磁化和相关性方面低至0.0016,在L=64.6的能量方面低至0.0063.
  • 生成的数据使准确的阶段分类成为可能,使用集体分类器使用F1得分高于0.99.

结论:

  • 拟议的深度生成框架为生成2D Ising模型旋转配置提供了一个计算效率高且可扩展的解决方案.
  • 该方法准确地捕获关键现象,并为物理系统分析提供高质量的合成数据.
  • 该方法展示了将基于物理的约束集成到科学模拟的深度学习中的力量.