An information-theoretic DII framework extracts low-dimensional nuclear modes governing conical intersection access and non-radiative decay from high-dimensional nonadiabatic dynamics simulations across multiple molecular systems.
The Journal of Chemical Physics , author=
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Applies causal inference to PCs from MD trajectories of two proteins to construct directed influence networks complementary to PCA and TICA.
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Machine learning the non-radiative decay modes in photochemical processes
An information-theoretic DII framework extracts low-dimensional nuclear modes governing conical intersection access and non-radiative decay from high-dimensional nonadiabatic dynamics simulations across multiple molecular systems.
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Investigating causality between principal components in protein dynamics
Applies causal inference to PCs from MD trajectories of two proteins to construct directed influence networks complementary to PCA and TICA.