标题： 规范协变神经网络用于夸克和胶子 显示英文标题

标题： Gauge covariant neural network for quarks and gluons

摘要： 我们提出了规范协变神经网络以及专门针对格点QCD的训练算法，旨在处理四维时空中的真实夸克和胶子。 我们表明，平滑处理过程可以被解释为具有固定参数的残差神经网络的扩展版本。 为了证明我们提出的神经网络的适用性，我们在双色QCD的背景下开发了一种自学习混合蒙特卡洛算法，得到的结果与传统的混合蒙特卡洛方法一致。 显示英文摘要

摘要： We propose gauge-covariant neural networks along with a specialized training algorithm for lattice QCD, designed to handle realistic quarks and gluons in four-dimensional space-time. We show that the smearing procedure can be interpreted as an extended version of residual neural networks with fixed parameters. To demonstrate the applicability of our neural networks, we develop a self-learning hybrid Monte Carlo algorithm in the context of two-color QCD, yielding outcomes consistent with those from the conventional Hybrid Monte Carlo approach.