Evidence of Inverse Mass Segregation in Dynamically Unevolved Young Open Clusters: A Three-Dimensional Analysis Based on Gaia DR3

This repository contains the source code and processed data supporting the findings in the manuscript "Evidence of Inverse Mass Segregation in Dynamically Unevolved Young Open Clusters: A Three-Dimensional Analysis Based on Gaia DR3", submitted to The Astrophysical Journal (ApJ). Contents: Cluster_Analysis_Toolkit.zip: Integrated package containing the final analysis pipeline (analysis_pipeline_v1.2_final.py), processed metrics, and README. Recommended for new users. final_metrics_complete.csv: Spatial and kinematic metrics for the 871 clusters analyzed. hunt24.csv & hunt24.zip: Master catalog and cluster member data (Hunt & Reffert 2024). Usage (for Version 1.2): Download and extract Cluster_Analysis_Toolkit.zip. Ensure the hunt24.csv file and the hunt24/ directory are placed in the same folder as the scripts. Run python analysis_pipeline_v1.2_final.py. Data Source & Reference: This work utilizes the open cluster catalog by Hunt & Reffert (2024) based on Gaia DR3 data (A&A, 682, A22). Update Log (v1.2): Integrated the final analysis pipeline and plotting utilities into a single toolkit for improved reproducibility. Updated plotting logic to use KDE distributions as requested by the referee. Expanded the analysis to a full 3D Bayesian reconstruction framework.本仓库包含了投稿至《天体物理学杂志》（The Astrophysical Journal, ApJ）的论文《动态未演化年轻疏散星团的逆质量分层证据：基于Gaia DR3的三维分析》的支撑性源代码与处理后数据。 内容清单： Cluster_Analysis_Toolkit.zip：集成化工具包，内含最终分析流程（analysis_pipeline_v1.2_final.py）、处理后的统计指标与README文档，推荐新用户使用。 final_metrics_complete.csv：本次分析涉及的871个星团的空间与运动学统计指标数据集。 hunt24.csv 与 hunt24.zip：主星表与星团成员数据（引自Hunt & Reffert 2024）。 使用方法（v1.2版本）： 1. 下载并解压Cluster_Analysis_Toolkit.zip。 2. 将hunt24.csv文件与hunt24目录放置于脚本所在的同一文件夹中。 3. 执行python analysis_pipeline_v1.2_final.py命令运行分析流程。 数据来源与参考文献：本研究使用基于Gaia DR3数据的Hunt & Reffert (2024) 疏散星星星表（《天文学与天体物理学》，682卷，A22）。 v1.2版本更新日志： 1. 将最终分析流程与绘图工具整合为单一工具包，以提升结果可复现性。 2. 按照审稿人要求，更新绘图逻辑以使用核密度估计（Kernel Density Estimation, KDE）分布。 3. 将分析拓展至完整的三维贝叶斯重建框架。