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Fourier analysis reveals why quantum neural networks learn poorly. Melbourne scientists bring answers
An international team from the University of Melbourne has for the first time mathematically described the frequency behavior of amplitude-encoded quantum neural networks. Their Fourier analysis reveals how noise and encoding methods affect the model's ability to learn — and offers concrete guidance for future development.