While quantum chemical simulations have been increasingly used as an invaluable source of information for atomistic model development, the high computational expenses typically associated with these techniques often limit thorough sampling of the systems of interest. It is therefore of great practical importance to use all available information as efficiently as possible, and in a way that allows for consistent addition of constraints that may be provided by macroscopic experiments. Here we propose a simple approach that combines information from configurational energies and forces generated in a molecular dynamics simulation to increase the effective number of samples. Subsequently, this information is used to optimize a molecular force field by minimizing the statistical distance similarity metric. We illustrate the methodology on an example of a trajectory of configurations generated in equilibrium molecular dynamics simulations of argon and water and compare the results with those based on the force matching method.

中文翻译：

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结合构型能量和力来优化分子力场

尽管量子化学模拟已越来越多地用作原子模型开发的宝贵信息来源，但通常与这些技术相关的高计算费用经常限制了对目标系统的彻底采样。因此，具有尽可能高的效率并以允许一致地添加可能由宏观实验提供的约束的方式使用所有可用信息具有非常重要的实践意义。在这里，我们提出了一种简单的方法，该方法结合了来自构型能量和分子动力学模拟中生成的力的信息，以增加有效样本数。随后，此信息用于通过最小化统计距离相似性度量来优化分子力场。