EDBench: Large-Scale Electron Density Data for Molecular Modeling
Hongxin Xiang · Ke Li · Mingquan Liu · Zhixiang Cheng · Bin Yao · Wenjie Du · Jun Xia · Li Zeng · Xin Jin · xiangxiang Zeng
Abstract
We propose EDBench, a large-scale, high-quality dataset of electron density (ED) designed to advance learning-based research at the electronic scale. EDBench comprises 3,359,472 drug-like molecules with corresponding ED distributions and a comprehensive set of quantum chemical properties, including energy components, orbital energies, and multipole moments, thus providing a solid foundation for systematically investigating the role of ED in molecular modeling. We outline the AI tasks, data rationale, acceleration potential, and concrete pathway to data-creation with cost and scalability of EDBench.
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