量子机器学习在化学化合物空间中的应用。
Quantum Machine Learning in Chemical Compound Space.
机构信息
Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials (MARVEL), Department of Chemistry, University of Basel, Klingelbergstrasse 80, 4056, Basel, Switzerland.
出版信息
Angew Chem Int Ed Engl. 2018 Apr 9;57(16):4164-4169. doi: 10.1002/anie.201709686. Epub 2018 Mar 14.
Rather than numerically solving the computationally demanding equations of quantum or statistical mechanics, machine learning methods can infer approximate solutions, interpolating previously acquired property data sets of molecules and materials. The case is made for quantum machine learning: An inductive molecular modeling approach which can be applied to quantum chemistry problems.
与其通过数值求解量子力学或统计力学中计算要求较高的方程，机器学习方法可以推断出近似解，对分子和材料的已有属性数据集进行插值。文中提出了量子机器学习的案例：一种可以应用于量子化学问题的归纳分子建模方法。
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