msmJAX: Fast and Differentiable Electrostatics on the GPU in Python

doi:10.1016/j.cpc.2026.110160

2026-04-12

PRE

DOI：10.1016/j.cpc.2026.110160

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摘要

En 中文

我们介绍了msmJAX，一个实现多级求和法与B样条插值的Python软件包，这是一种线性缩放算法，用于在粒子模拟中高效计算静电和其他长程相互作用。基于JAX框架构建，msmJAX自然地与正在改变化学和材料科学的机器学习方法集成，同时本身也是一种强大的工具。它结合了高性能与Python的易用性，便于在GPU上部署，并支持自动微分。我们概述了msmJAX的模块化设计，使用户能够适应或扩展代码，并展示了基准测试和示例，包括线性缩放的验证以及其在分子动力学模拟中的稳定性演示。

Keyword:

multilevel summation method

B-spline interpolation

electrostatic interactions

GPU computing

automatic differentiation

期刊

Computer Physics Communications

IF:

3.4

论文数:

1.2W

被引数:

3.7W

机构

TU Wien

学者数:

344

论文数: 145

被引数: 1.1W

CSIC and Universidad de Zaragoza

学者数:

论文数: 33

被引数: 0

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