Causal analysis of water MD simulations shows translational motions drive orientational dynamics in supercooled HDL but remain decoupled at ambient conditions, revealing an emergent arrow of time in fluctuation couplings.
Journal of Chemical Theory and Computation , author=
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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.
A neural-network temperature classification task plus XAI is used to benchmark 16 structural descriptors for their ability to capture temperature-dependent local order in supercooled water.
citing papers explorer
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Causality in Liquid Water as a Hallmark of Emergent Glassy Dynamics
Causal analysis of water MD simulations shows translational motions drive orientational dynamics in supercooled HDL but remain decoupled at ambient conditions, revealing an emergent arrow of time in fluctuation couplings.
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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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Machine learning evaluation of structural descriptors for supercooled water
A neural-network temperature classification task plus XAI is used to benchmark 16 structural descriptors for their ability to capture temperature-dependent local order in supercooled water.