five

Nuclear Mass Predictions through Neural Networks Incorporating Neutron and Proton Separation Energy Constraints

收藏
DataCite Commons2025-12-11 更新2026-05-05 收录
下载链接:
https://www.scidb.cn/detail?dataSetId=61f8e7fa35414978ba18d644578a35c3
下载链接
链接失效反馈
官方服务:
资源简介:
This dataset is generated by combining nuclear mass theoretical models with machine-learning techniques. The data production process consists of two main steps: (1) constructing training samples based on existing nuclear mass databases (such as AME2020 and PCF-PK1); and (2) training and predicting with four independently built artificial neural network models (ANN1–ANN4).The training samples cover a range of nuclides determined by the proton number Z and neutron number N, spanning from light nuclei to the superheavy region. Since the ANN1–ANN4 networks are trained independently, the dataset provides four separate sets of prediction results, which can be used to reflect uncertainties arising from model-structure variations.Data FilesThe dataset contains four primary data files, corresponding to the prediction results of the four neural network models:ANN1_extra.txtANN2_extra.txtANN3_extra.txtANN4_extra.txtAll files are in TXT format (comma-separated text) and can be opened with any text editor, Microsoft Excel, or scientific computing tools such as Python/pandas or MATLAB, without requiring any special software.Each file contains the following columns:Z, N: proton number and neutron number of the nucleus;E: binding energy;Sn, S2n: one-neutron and two-neutron separation energies;Sp, S2p: one-proton and two-proton separation energies.All binding energies and separation energies are given in MeV.

本数据集通过结合核质量理论模型与机器学习技术生成。数据生成流程主要包含两个核心步骤:(1) 基于现有核质量数据库(如AME2020与PCF-PK1)构建训练样本集;(2) 采用四个独立构建的人工神经网络(Artificial Neural Network, ANN)模型(ANN1–ANN4)开展训练与预测工作。 训练样本覆盖由质子数Z与中子数N定义的各类核素,范围涵盖轻核至超重核区域。由于ANN1至ANN4网络为独立训练所得,本数据集提供四组独立的预测结果,可用于反映模型结构差异带来的不确定性。 数据文件 本数据集包含四个主要数据文件,分别对应四个人工神经网络模型的预测结果:ANN1_extra.txt、ANN2_extra.txt、ANN3_extra.txt、ANN4_extra.txt。所有文件均为TXT格式(逗号分隔文本),可通过任意文本编辑器、Microsoft Excel,或Python/pandas、MATLAB等科学计算工具打开,无需特殊软件。 每个文件包含以下列: Z、N:原子核的质子数与中子数; E:结合能; Sn、S2n:单中子分离能与双中子分离能; Sp、S2p:单质子分离能与双质子分离能。 所有结合能与分离能的单位均为MeV。
提供机构:
Science Data Bank
创建时间:
2025-12-11
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作