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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2026 2verdicts
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The paper establishes an exact N-centered ensemble DFT formalism unifying neutral and charged excitations and introduces three practical strategies: weight-dependent scaling of ground-state functionals, quasi-degenerate ensemble perturbation theory, and quantum bath embedding for excited states.
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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.
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Ensemble density functional theory of excited states: Exact N-centered formalism and practical opportunities
The paper establishes an exact N-centered ensemble DFT formalism unifying neutral and charged excitations and introduces three practical strategies: weight-dependent scaling of ground-state functionals, quasi-degenerate ensemble perturbation theory, and quantum bath embedding for excited states.