Vibrational spectroscopy is key in probing the interplay between the structure and dynamics of aqueous systems. To map different regions of experimental spectra to the microscopic structure of a system, it is important to combine them with first-principles atomistic simulations that incorporate the quantum nature of nuclei. Here we show that the large cost of calculating the quantum vibrational spectra of aqueous systems can be dramatically reduced compared with standard path integral methods by using approximate quantum dynamics based on high-order path integrals. Together with state-of-the-art machine-learned electronic properties, our approach gives an excellent description not only of the infrared and Raman spectra of bulk water but also of the 2D correlation and the more challenging sum-frequency generation spectra of the water–air interface. This paves the way for understanding complex interfaces such as water encapsulated between or in contact with hydrophobic and hydrophilic materials through robust and inexpensive surface-sensitive and multidimensional spectra with first-principles accuracy.

中文翻译：

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具有高阶路径积分的水的高效量子振动光谱：从本体到界面

振动光谱是探索水性体系结构和动力学之间相互作用的关键。要将实验光谱的不同区域映射到系统的微观结构，重要的是将它们与包含原子核量子性质的第一性原理原子模拟相结合。在这里，我们表明，通过使用基于高阶路径积分的近似量子动力学，与标准路径积分方法相比，可以显着降低计算水性体系量子振动谱的大量成本。结合最先进的机器学习电子特性，我们的方法不仅可以很好地描述散装水的红外和拉曼光谱，还可以很好地描述水的二维相关性和更具挑战性的和频生成光谱——空中接口。