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大型活动空间的轨道优化通过AI加速器
Örs Legeza1,2,3, Andor Menczer1,4, Ádám Ganyecz1
1Strongly Correlated Systems Lendület Research Group, Wigner Research Centre for Physics, H-1525 Budapest, Hungary.
Journal of chemical theory and computation
|June 13, 2025
概括
我们开发了一种高效的轨道优化方法,将GPU加速密度矩阵重规范化组 (DMRG) 与完整的活性空间自相一致场 (CAS-SCF) 结合起来,用于大型量子化学系统. 这种方法可以对前所未有的系统大小进行准确的计算,从而推进强烈相关的分子系统研究.
科学领域:
- 量子化学 是一个量子化学.
- 计算化学计算化学
- 材料科学 材料科学 材料科学
背景情况:
- 准确的电子结构计算对于理解分子行为至关重要.
- 大规模的活跃空间计算在计算上要求很高,这限制了它们的应用.
- 需要有效的方法来解决强烈相关的系统.
研究的目的:
- 为量子化学提出一个高效的轨道优化程序.
- 为了将GPU加速的DMRG与CAS-SCF相结合,用于大型活动空间.
- 为了能够对前所未有的系统大小进行准确的计算.
主要方法:
- 使用高GPU加速,自旋适应的密度矩阵重规范化组 (DMRG) 方法.
- 集成的DMRG与完整的活性空间自相一致的场 (CAS-SCF) 方法.
- 在NVIDIA DGX-A100和DGX-H100硬件上进行了基于CAS-SCF的轨道优化.
主要成果:
- 取得了前所未有的CAS大小,最高可达CAS (82,82) 和以上.
- 证明了准确的DMRG计算对于融合的CAS-SCF能量的关键性.
- 观察到优化轨道对铁硫复合物的DMRG参数的敏感依赖.
结论:
- 开发的DMRG-SCF方法可以对大型活动空间进行准确的计算.
- 这种方法显著减少了复杂分子系统研究所需的时间.
- 开辟了解决强烈相关的分子系统的新途径.
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