论文标题
使用贝叶斯热力学整合计算阶段和面
Counting Phases and Faces Using Bayesian Thermodynamic Integration
论文作者
论文摘要
我们引入了一种新的方法来重建两参数统计力学系统中热力学函数和相边界。我们的方法基于在外部参数的空间上以后验分布来表达Fisher度量，并通过凸功能的Hessian近似度量场。我们使用所提出的方法准确地重建了ISING模型的分区函数和相图，以及确切的可解决的非平衡tasep，而没有任何有关模型显微镜规则的先验知识。我们还展示了如何使用我们的方法可视化StyleGAN模型的潜在空间并评估生成的图像的可变性。
We introduce a new approach to reconstruction of the thermodynamic functions and phase boundaries in two-parametric statistical mechanics systems. Our method is based on expressing the Fisher metric in terms of the posterior distributions over a space of external parameters and approximating the metric field by a Hessian of a convex function. We use the proposed approach to accurately reconstruct the partition functions and phase diagrams of the Ising model and the exactly solvable non-equilibrium TASEP without any a priori knowledge about microscopic rules of the models. We also demonstrate how our approach can be used to visualize the latent space of StyleGAN models and evaluate the variability of the generated images.
