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相关概念视频

Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

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Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
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Poisson's And Laplace's Equation01:25

Poisson's And Laplace's Equation

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The electric potential of the system can be calculated by relating it to the electric charge densities that give rise to the electric potential. The differential form of Gauss's law expresses the electric field's divergence in terms of the electric charge density.
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Distributed Loads01:19

Distributed Loads

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Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
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Trends in Lattice Energy: Ion Size and Charge02:54

Trends in Lattice Energy: Ion Size and Charge

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An ionic compound is stable because of the electrostatic attraction between its positive and negative ions. The lattice energy of a compound is a measure of the strength of this attraction. The lattice energy (ΔHlattice) of an ionic compound is defined as the energy required to separate one mole of the solid into its component gaseous ions. For the ionic solid sodium chloride, the lattice energy is the enthalpy change of the process:
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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Carrier Transport01:21

Carrier Transport

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The generation of electrical current in semiconductors is fundamentally driven by two mechanisms: drift and diffusion. These processes are essential for the functionality and performance of semiconductor-based devices.
Drift Current:
The drift of charge carriers is started by an external electric field (E). Charged particles, such as electrons and holes, experience an acceleration between collisions with lattice atoms. For electrons, this results in a drift velocity (vd) given by:
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Updated: Jan 10, 2026

Image-based Lagrangian Particle Tracking in Bed-load Experiments
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Image-based Lagrangian Particle Tracking in Bed-load Experiments

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负载平衡扩散蒙特卡洛方法与格子规范化.

Kousuke Nakano1, Sandro Sorella2, Michele Casula3

  • 1Center for Basic Research on Materials (CBRM), National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047, Japan.

The Journal of chemical physics
|November 21, 2025
PubMed
概括
此摘要是机器生成的。

一个新的负载平衡格子调节扩散蒙特卡罗 (LRDMC) 算法提高了量子蒙特卡罗 (QMC) 模拟的并行效率. 这种方法提高了现代超级计算机的硬件利用率,实现了高平行效率和加快复杂计算的速度.

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科学领域:

  • 计算物理 计算物理
  • 量子化学 是一个量子化学.
  • 高性能计算 高性能计算

背景情况:

  • 从一开始,量子蒙特卡罗 (QMC) 提供了多体施罗丁格方程的随机解决方案,没有单体近似.
  • 扩散蒙特卡洛 (DMC),一个QMC的变体,可靠地投影到地面状态使用固定节点近似.
  • 格子调节扩散蒙特卡洛 (LRDMC) 是一个实际的DMC实现,但在并行化中存在负载失衡问题.

研究的目的:

  • 开发和介绍一种新的负载平衡LRDMC算法.
  • 解决和减轻传统LRDMC中固有的负载不平衡.
  • 在现代架构上显著提高弱缩放并行效率.

主要方法:

  • 实施了一种新的LRDMC算法,用于内在负载平衡.
  • 使用散步器 (Nw) 组合在高性能计算系统上进行并行处理.
  • 在使用NVIDIA A100 GPU的莱昂纳多超级计算机上对水甲复合体的结合能计算测试了算法.

主要成果:

  • 负载平衡的LRDMC算法产生了与传统方法一致的结果.
  • 在512个GPU (Nw = 51,200) 上实现了高并行效率 (∼98%).
  • 与传统的LRDMC相比,与相同的步行者数量相比,表现出×1.24的加速度,甚至与减少的步行者 (Nw = 400) 相比,×1.18的加速度.

结论:

  • 开发的负载平衡LRDMC算法有效地解决了平行QMC模拟中的负载失衡问题.
  • 这种进步导致了更高的硬件利用率和大规模计算资源的并行效率.
  • 该方法显示了加速计算物理和化学中的复杂量子力学计算的巨大潜力.