发表机构
LUX, Observatoire de Paris, CNRS, PSL; Astronomy Department, Raderon AI Lab., BC.; Shandong Key Laboratory of Space Environment and Exploration Technology, Institute of Space Sciences, School of Space Science and Technology, Shandong University; Binary Systems of South and North (BSN) Project; Independent Researcher; Çanakkale Onsekiz Mart University, Faculty of Science, Department of Physics; Çanakkale Onsekiz Mart University, Astrophysics Research Center and Ulupnar Observatory; Fatih Sultan Mehmet Vakif University, Department of History of Science（巴黎天文台; 不列颠哥伦比亚大学天文学系雷德伦人工智能实验室; 山东大学空间科学与技术学院空间科学研究所山东省空间环境与探测技术重点实验室; 南北双星项目；独立研究者; 恰纳卡莱18马尔特大学理学院物理系; 恰纳卡莱18马尔特大学天体物理学研究中心乌鲁帕纳尔天文台; 法提赫苏丹梅赫梅特基金会大学科学史系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究基于W UMa型相接双星样本，利用无监督聚类和随机森林回归，发现填充因子分布呈三类结构，质量比为主导预测因子，反映连续几何演化而非离散物理状态。
AI 中文摘要
相接双星系统表现出由质量转移、角动量损失（AML）和洛希几何共同支配的复杂演化行为。填充因子（$f$）被广泛用作描述过相接程度的指标，然而其物理和统计作用在文献中的定义并不统一。我们利用一个汇编的观测样本，即W UMa型相接双星，构建了一个基于$f$及其与基本系统参数关系的数据驱动分类框架。对一维$f$分布应用无监督聚类，揭示出一个稳健的三类结构，分别对应浅度、中度和深度相接形态。统计确定的边界位于$f \simeq 0.257$和$f \simeq 0.561$，且轮廓系数稳定为$S \simeq 0.613$。该分类的稳定性通过$f$的扰动检验和参数条件样本得到确认。随机森林回归模型表明，$f$中方差的60.7%可由所考虑的物理和几何系统参数解释，其中几何参数提供了最大的预测贡献。在所考虑的参数中，质量比成为主导预测因子。因此，所识别的子类似乎反映了一个连续的几何序列，而非离散的物理状态，该序列由质量转移和角动量损失下洛希等势形态的渐进演化所支配。值得注意的是，分隔中度和深度相接系统的第二个边界比第一个边界表现出更低的稳定性，这表明向深度相接的过渡可能对分析样本的物理组成更为敏感。
英文摘要
Contact binary systems exhibit complex evolutionary behavior governed by mass transfer, angular momentum loss (AML), and Roche geometry. The fillout factor ($f$) is widely used as a descriptor of the degree of overcontact, yet its physical and statistical role remains nonuniformly defined across the literature. We used a compiled observational sample of W UMa-type contact binaries to construct a data-driven classification framework based on $f$ and its relation to fundamental system parameters. Unsupervised clustering applied to the one-dimensional $f$ distribution reveals a robust three-class structure corresponding to shallow-, medium-, and deep-contact configurations. The statistically determined boundaries are located at $f \simeq 0.257$ and $f \simeq 0.561$, with a stable silhouette score of $S \simeq 0.613$. The stability of this classification is confirmed through perturbation tests in $f$ and parameter-conditioned samples. A random forest regression model shows that 60.7\% of the variance in $f$ can be explained by the considered physical and geometric system parameters, with geometric parameters providing the largest predictive contribution. Among the considered parameters, the mass ratio emerges as the dominant predictor. The identified subclasses therefore appear to reflect a continuous geometric sequence rather than discrete physical states, governed by the progressive evolution of the Roche equipotential configuration under mass transfer and AML. Notably, the second boundary separating medium- and deep-contact systems shows lower stability than the first boundary, suggesting that the transition toward deep contact may be more sensitive to the physical composition of the analyzed sample.
CommentsAccepted by the A&A journal
