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.

中文翻译：

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Ising系统受限玻尔兹曼机模型的精度

受限玻尔兹曼机 (RBM) 为物理系统建模提供了一个通用框架，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伊辛自旋系统计算的影响。在统计量的准确性（例如比热）与能量和磁化强度的联合分布的准确性之间确定权衡。因此，RBM ​​的最佳结构本质上取决于它所应用的物理问题。