Musil Félix, Zaporozhets Iryna, Noé Frank, Clementi Cecilia, Kapil Venkat
Department of Physics, Freie Universität Berlin, Arnimallee 12, 14195 Berlin, Germany.
Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom.
J Chem Phys. 2022 Nov 14;157(18):181102. doi: 10.1063/5.0120386.
The vibrational spectra of condensed and gas-phase systems are influenced by thequantum-mechanical behavior of light nuclei. Full-dimensional simulations of approximate quantum dynamics are possible thanks to the imaginary time path-integral (PI) formulation of quantum statistical mechanics, albeit at a high computational cost which increases sharply with decreasing temperature. By leveraging advances in machine-learned coarse-graining, we develop a PI method with the reduced computational cost of a classical simulation. We also propose a simple temperature elevation scheme to significantly attenuate the artifacts of standard PI approaches as well as eliminate the unfavorable temperature scaling of the computational cost. We illustrate the approach, by calculating vibrational spectra using standard models of water molecules and bulk water, demonstrating significant computational savings and dramatically improved accuracy compared to more expensive reference approaches. Our simple, efficient, and accurate method has prospects for routine calculations of vibrational spectra for a wide range of molecular systems - with an explicit treatment of the quantum nature of nuclei.
凝聚相和气相系统的振动光谱受轻核量子力学行为的影响。借助量子统计力学的虚时路径积分(PI)公式,全维近似量子动力学模拟成为可能,尽管计算成本很高,且随着温度降低而急剧增加。通过利用机器学习粗粒化方面的进展,我们开发了一种计算成本降低至经典模拟水平的PI方法。我们还提出了一种简单的升温方案,以显著减少标准PI方法的伪影,并消除计算成本对温度的不利缩放。我们通过使用水分子和体相水的标准模型计算振动光谱来说明该方法,结果表明与更昂贵的参考方法相比,计算成本显著节省,精度大幅提高。我们简单、高效且准确的方法有望用于广泛分子系统振动光谱的常规计算——同时明确处理核的量子性质。