A neural network trained on synthetic random Hamiltonians purifies noisy SASE FEL photoelectron spectra, recovering the ideal Fourier-limited reference spectrum for unseen atoms and molecules.
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Purifying electron spectra from noisy pulses with machine learning using synthetic Hamilton matrices
A neural network trained on synthetic random Hamiltonians purifies noisy SASE FEL photoelectron spectra, recovering the ideal Fourier-limited reference spectrum for unseen atoms and molecules.