NTangled

NTangled数据集是由洛斯阿拉莫斯国家实验室理论部的研究人员创建的，用于量子机器学习。该数据集包含不同数量和类型的多体纠缠量子态，旨在通过量子神经网络生成这些态，并用于监督学习分类任务。NTangled数据集的创建涉及训练量子神经网络以生成具有特定纠缠值的量子态，这些态随后用于评估量子机器学习模型的性能。数据集的应用领域包括量子计算和量子信息处理，特别是在探索量子优势和解决量子多体问题方面。

The NTangled dataset was developed by researchers from the Theoretical Division of Los Alamos National Laboratory for quantum machine learning research. This dataset includes multipartite entangled quantum states with varying quantities and types, aiming to generate such states through quantum neural networks and support supervised learning classification tasks. The creation of the NTangled dataset involves training quantum neural networks to produce quantum states with specific entanglement values, which are then utilized to assess the performance of quantum machine learning models. The application fields of this dataset cover quantum computing and quantum information processing, especially in exploring quantum advantage and addressing quantum many-body problems.