论文标题
ISING系统的限制玻尔兹曼机器模型的准确性
The Accuracy of Restricted Boltzmann Machine Models of Ising Systems
论文作者
论文摘要
受限的玻尔兹曼机器（RBM）提供了建模物理系统的一般框架，但它们的行为取决于超参数，例如学习率，隐藏节点的数量和阈值函数的形式。因此，本文详细研究了这些参数对ISINS自旋系统计算的影响。在统计量的准确性（例如特定热量）和能量和磁化的联合分布的准确性之间确定了权衡。因此，RBM的最佳结构在本质上取决于应用其应用的物理问题。
Restricted Boltzmann machine (RBM) provide a general framework for modeling physical systems, but their behavior is dependent on hyperparameters such as the learning rate, the number of hidden nodes and the form of the threshold function. This article accordingly examines in detail the influence of these parameters on Ising spin system calculations. A tradeoff is identified between the accuracy of statistical quantities such as the specific heat and that of the joint distribution of energy and magnetization. The optimal structure of the RBM therefore depends intrinsically on the physical problem to which it is applied.
