标题： 星系考古学中潜在变量的因果发现 显示英文标题

标题： Causal Discovery of Latent Variables in Galactic Archaeology

摘要： 银河考古学——恒星迁移历史的研究——为星系形成和演化提供了见解。 然而，建立可观察的恒星属性与其出生条件之间的因果关系仍然具有挑战性，因为像出生半径这样的关键属性无法直接观测。 我们采用基于排名的潜在因果发现（RLCD）来揭示模拟银河系天体化学动力学的因果结构。 仅使用五个可观察属性（金属量、年龄和轨道参数），我们以纯粹的数据驱动方式恢复了一个包含两个潜在节点的因果图，这两个潜在节点对应于真实的物理属性：恒星的出生半径和引导半径。 我们的研究展示了因果发现模型在天体物理学中的潜力。 显示英文摘要

摘要： Galactic archaeology--the study of stellar migration histories--provides insights into galaxy formation and evolution. However, establishing causal relationships between observable stellar properties and their birth conditions remains challenging, as key properties like birth radius are not directly observable. We employ Rank-based Latent Causal Discovery (RLCD) to uncover the causal structure governing the chemodynamics of a simulated Milky Way galaxy. Using only five observable properties (metallicity, age, and orbital parameters), we recover in a purely data-driven manner a causal graph containing two latent nodes that correspond to real physical properties: the birth radius and guiding radius of stars. Our study demonstrates the potential of causal discovery models in astrophysics.