Predictive Free Energy Simulations Through Hierarchical Distillation of Quantum Hamiltonians
通过量子哈密顿量的分层蒸馏进行预测自由能模拟
机构 * Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA(化学与化工系,加州理工学院,帕萨迪纳,CA,91125,USA) ; Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA(化学工程,加州理工学院,帕萨迪纳,CA,91125,USA)
AI总结 本文提出一种分层机器学习框架,通过蒸馏少量高精度量子计算知识,构建粗粒化机器学习量子哈密顿量,实现高精度自由能模拟,验证了弱酸质子解离常数和酶反应速率的计算准确性。