1. Spectral Denoising for Accelerated Analysis of Correlated Ionic Transport
- Author
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Nicola Molinari, Boris Kozinsky, Ian Leifer, Mordechai Kornbluth, Aris Marcolongo, and Yu Xie
- Subjects
Mean squared displacement ,Physics ,Molecular dynamics ,Noise reduction ,Computation ,General Physics and Astronomy ,Ionic bonding ,Ionic conductivity ,Statistical physics ,Covariance ,Matrix decomposition - Abstract
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 systematic reduction of 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.
- Published
- 2021
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