光谱去噪用于相关离子输运的无监督分析
Spectral denoising for unsupervised analysis of correlated ionic transport
摘要：
从分子动力学中计算相关离子输运性质的Green-Kubo形式主义是昂贵的，因为人们不能依赖于负担得起的均方位移方法。我们使用短时间离子位移协方差的谱分解来学习一组编码相关结构的扩散本征模，并形成分析离子轨迹的基础。这允许系统地减少不确定性，并加速具有稳态相关结构的系统中的离子电导率的计算。我们提供的方法的鲁棒性的数学和数值证明，并证明它对现实的电解质材料。
英文摘要：
Computation of correlated ionic transport properties from molecular dynamics in the Green-Kubo formalism is expensive as one cannot rely on the affordable mean square displacement approach. We use spectral decomposition of the short-time ionic displacement covariance to learn a set of diffusion eigenmodes that encode the correlation structure and form a basis for analyzing the ionic trajectories. This allows to systematically reduce the uncertainty and accelerate computations of ionic conductivity in systems with a steady-state correlation structure. We provide mathematical and numerical proofs of the method's robustness, and demonstrate it on realistic electrolyte materials.
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