Circuit Harmonic Matrices: A Spectral Framework for Quantum Machine Learning
The work introduces a data-agnostic framework mapping quantum circuits into a single architecture matrix C based on joint harmonic representations of input and parameters. This matrix explicitly links circuit structure to correlations among learnable features and the geometry of training kernels, showing how circuit design dictates accessible learning spaces.