A symmetry-based analysis of nonadiabatic dynamics near conical intersections predicts that nodal-line structures are robust only in highly symmetric settings and break when symmetry is reduced.
arXiv preprint arXiv:2508.05263 , year=
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A Gaussian mixture model is used to learn spectral densities from 2DES experiments, enabling extraction of vibronic couplings, spectral extrapolation, and optimized experiment selection across simulated and experimental systems.
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Symmetry and Topology in Wavepacket Dynamics near Conical Intersections
A symmetry-based analysis of nonadiabatic dynamics near conical intersections predicts that nodal-line structures are robust only in highly symmetric settings and break when symmetry is reduced.
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Streamlining Analysis and Design of Two-Dimensional Electronic Spectroscopy using Machine Learning
A Gaussian mixture model is used to learn spectral densities from 2DES experiments, enabling extraction of vibronic couplings, spectral extrapolation, and optimized experiment selection across simulated and experimental systems.