Kohn-Sham density functional theory (DFT) remains the workhorse of ab initio materials simulation, yet cubic computational and quadratic memory scaling have confined calculations to a few hundred to thousands of atoms, spanning only nanometers, far below experimentally relevant length scales. We introduce XLSDFT, a lin...
Qi-Men Xu, Yu Zhang, Di-Xing Ni et al.· 0 citations
LineShine is presented, a newly deployed exascale supercomputer whose online acceleration architecture provides a new design point for converged HPC and AI and demonstrates that its balanced architecture and software stack can translate system capability into high throughput, robust scalability, and sustained scientifi...
Accurate prediction of electronic Hamiltonians would enable broad property inference while avoiding the high computational cost of Density Functional Theory (DFT). However, progress toward general-purpose materials foundation models is limited by a data bottleneck: existing Hamiltonian datasets are typically small, lac...
Yuewen Huang, Pin Chen, Yutong Lu· Proceedings of the 32nd ACM...· 0 citations
Learned electronic states are usually evaluated by prediction error, even though their intended use is to accelerate the self-consistent-field (SCF) loop of density functional theory (DFT). We ask whether lower offline error actually yields a better SCF initializer. We construct $\rho$HD-43K, a 43,851-crystal DFT corpu...
These findings provide descriptive benchmarks for ASD surveillance, early recognition, service organization, and equitable healthcare planning and should not be interpreted as direct measures of service quality, unmet need, or injury risk.
Xue-Quan Liang, Wen-Yi Jin, Xin-Yang Bu et al.· Frontiers in Public Health· 0 citations
Purpose Anxiety and depressive disorders constitute major contributors to global mental health burdens, disproportionately affecting 10-24-year-olds during critical neurodevelopmental windows. Despite their substantial disease burden, persistent treatment gaps and inequitable resource allocation remain worldwide. This...
Ming-Lu Yuan, Xue-Quan Liang, Wen-Yi Jin et al.· Frontiers in Public Health· 0 citations
Accurate prediction of electronic Hamiltonians would enable broad property inference while avoiding the high computational cost of Density Functional Theory (DFT). However, progress toward general-purpose materials foundation models is limited by a data bottleneck: existing Hamiltonian datasets are typically small, lac...
Yuewen Huang, Pin Chen, Yutong Lu· Proceedings of the 32nd ACM...· 0 citations
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