4D SU(3) 轨则场的神经网络轨则场变换

arXiv - PHYS - High Energy Physics - Lattice Pub Date : 2024-05-30 DOI:arxiv-2405.19692

Xiao-Yong Jin

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引用次数: 0

摘要

我们构建的神经网络适用于任何李群，并保持量规协方差，从而实现平滑、可逆的量规场变换。我们为 4D SU(3) 格规场实现了这些变换，并探索了它们在 HMC 中的应用。我们的重点是开发损失函数和优化变换。我们展示了对 HMC 分子动力学的影响，并讨论了该方法的可扩展性。

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Neural Network Gauge Field Transformation for 4D SU(3) gauge fields

We construct neural networks that work for any Lie group and maintain gauge covariance, enabling smooth, invertible gauge field transformations. We implement these transformations for 4D SU(3) lattice gauge fields and explore their use in HMC. We focus on developing loss functions and optimizing the transformations. We show the effects on HMC's molecular dynamics and discuss the scalability of the approach.

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arXiv - PHYS - High Energy Physics - Lattice

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