Classifying the generation and formation channels of dynamically-formed gravitational-wave events

This dataset contains all the simulations of dynamically-formed binaries performed with the software rapster, together with trained machine-learning classification models from (Antonelli, Kritos et al, in prep.), see the public codes online. All items starting with "mergers_*" are simulations of clusters and they follow the structure reported in the documentation of rapster. The simulations differ in the choice of the hyperparameters for the distribution of the cluster mass, half-mass radius and initial spin distribution for the binaries. All items starting from "RFClassifier_*" are machine-learning classification models that use a Random Forest Classifier and that are trained with the simulations above. The models ending with "*_gen" predict the generation of the black holes, those with "*_form" predict their formation channels.本数据集涵盖所有使用rapster软件完成的动力学形成双星系统的模拟结果，以及Antonelli、Kritos等（待发表）工作中提出的经训练机器学习分类模型，相关公开代码可在线查阅。所有以"mergers_*"开头的条目均为星团模拟样本，其数据结构严格遵循rapster官方文档规定的格式。本次模拟在超参数配置上存在差异，涉及星团质量分布、半质量半径以及双星初始自旋分布三类超参数的选择。所有以"RFClassifier_*"开头的条目均为基于上述模拟结果训练得到的随机森林分类器（Random Forest Classifier）机器学习分类模型。其中，后缀为"*_gen"的模型用于预测黑洞的生成代次，后缀为"*_form"的模型则用于预测黑洞的形成通道。