论文标题
在具有持久同源性的旋转模型中找到隐藏的顺序
Finding hidden order in spin models with persistent homology
论文作者
论文摘要
持续的同源性（PH）是应用数学的相对较新的领域，研究了离散数据的组件和形状。在这项工作中，我们证明pH可以用作通用框架，以识别自旋模型中的相位，包括隐藏顺序，例如自旋列有序和自旋液体。通过将少量的自旋配置转换为条形码，我们获得了配置空间的描述性图片。使用降低尺寸减少条形码空间来彩色空间，从而可视化相图。
Persistent homology (PH) is a relatively new field in applied mathematics that studies the components and shapes of discrete data. In this work, we demonstrate that PH can be used as a universal framework to identify phases in spin models, including hidden order such as spin nematic ordering and spin liquids. By converting a small number of spin configurations to barcodes we obtain a descriptive picture of configuration space. Using dimensionality reduction to reduce the barcode space to color space leads to a visualization of the phase diagram.
