iPINN for Broadband CARS Phase Retrieval: A Framework for Function Approximation and Inverse Modeling Problems in Nonlinear Spectroscopy
iPINN is introduced, a inverse physics-informed neural network that predicts Lorentzian peak parameters from raw BCARS spectra and reconstructs the resonant susceptibility through a differentiable analytical forward model and supports robust phase retrieval across measurement conditions.
R. Vulchi, Carl Messerschmidt, Mohammadsadegh Vafaeinezhad et al.
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