论文标题
光谱降解用于无监督的相关离子传输分析
Spectral denoising for unsupervised analysis of correlated ionic transport
论文作者
论文摘要
从绿色kubo形式主义中分子动力学的相关离子传输特性的计算很昂贵，因为人们不能依靠负担得起的均方根位移方法。我们使用短期离子位移协方差的光谱分解来学习一组编码相关结构的扩散本征模，并构成分析离子轨迹的基础。这允许系统地减少具有稳态相关结构的系统中离子电导率的不确定性和加速计算。我们提供了该方法鲁棒性的数学和数值证明，并在逼真的电解质材料上证明了这一点。
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.
