Hierarchical Fourier Approximation for Variational Quantum Distribution Learning
An end-to-end expected learning guarantee is proved where the approximation term is determined by the omitted Fourier mass, while a normalized unbiased estimator yields an explicit statistical bound for empirical truncations.
Taha Hoseinpour Asli, Sajjad Hashemian, Ebrahim Ardeshir-Larijani
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