AI 中文总结
该研究探讨机器学习在热亚矮星与白矮星的探测、表征及物理解释中的应用，结合多波段观测数据可高效研究致密恒星的演化，凸显高级算法在晚期恒星演化研究中的重要作用。
AI 中文摘要
大规模天文巡天的快速发展与数据驱动分析技术的进步，已改变了晚期恒星演化的研究模式。现代观测设备正产生海量的测光、光谱和天体测量数据，为银河系内致密恒星族群的系统研究提供了可能。热亚矮星与白矮星是这些演化晚期阶段最重要的示踪天体：热亚矮星是氦核燃烧的示踪体，反映由双星驱动的晚期恒星演化；白矮星则是低质量和中等质量恒星的最终演化终点。这些致密天体为研究恒星内部结构、双星演化及行星系统的长期命运提供了重要实验室。本文探讨机器学习的最新进展如何应用于热亚矮星与白矮星的探测、表征，以及结合后续光谱观测和建模对其进行物理解释。通过将测光、光谱和时域观测数据与这些计算工具相结合，目前已可高效发现稀有天体、探测恒星变异性，并探测致密恒星的内部结构与演化路径。最终，这些进展凸显了高级算法在支持恒星演化最后阶段研究中的日益重要作用，前提是其输出结果需通过物理观测值进行验证。
英文摘要
The rapid growth of large-scale astronomical surveys and advances in data-driven analysis techniques have transformed the study of late-stage stellar evolution. Modern facilities are producing large volumes of photometric, spectroscopic, and astrometric data, enabling systematic investigations of compact stellar populations across the Milky Way. Among the most important tracers of these advanced evolutionary phases are hot subdwarfs and white dwarfs: hot subdwarfs are core-helium-burning tracers of late, binary-driven stellar evolution, while white dwarfs represent the final evolutionary endpoint of low- and intermediate-mass stars. These compact objects provide important laboratories for studying stellar interiors, binary evolution, and the long-term fate of planetary systems. This paper explores how recent advances in machine learning are being applied to the detection, characterization, and, when combined with follow-up spectroscopy and modeling, the physical interpretation of hot subdwarfs and white dwarfs. By combining photometric, spectroscopic, and time-domain observations with these computational tools, it is now possible to efficiently discover rare objects, detect stellar variability, and probe the internal structure and evolutionary pathways of compact stars. Ultimately, these developments highlight the growing role of advanced algorithms in supporting the study of the final stages of stellar evolution, provided their outputs are validated against physical observables.
CommentsAccepted for publication in MDPI Universe; 15 pages, 3 figures, 3 tables
