标题： 机器学习在格点量子引力中的应用 显示英文标题

标题： Machine learning in lattice quantum gravity

摘要： 使用来自四维因果动态三角剖分蒙特卡洛模拟的数值数据，我们研究了如何使用自动机器学习算法来识别在格点量子引力中观察到的不同量子几何相之间的转变。我们测试了七个监督和七个无监督的机器学习模型，并发现其中大多数在该任务中非常成功，甚至超过了基于序参数的标准方法。 显示英文摘要

摘要： Using numerical data coming from Monte Carlo simulations of four-dimensional Causal Dynamical Triangulations, we study how automated machine learning algorithms can be used to recognize transitions between different phases of quantum geometries observed in lattice quantum gravity. We tested seven supervised and seven unsupervised machine learning models and found that most of them were very successful in that task, even outperforming standard methods based on order parameters.