qubithub/quantum-kernel-svm

Trains a classical Support Vector Machine on a kernel matrix computed from quantum circuits. The ZZ feature map encodes data into an exponentially large Hilbert space via entangling RZ(x_i·x_j·π) gates, and the inversion test measures K(x,y) = |⟨φ(x)|φ(y)⟩|² as the all-zeros probability. Includes synthetic data generation, SVM dual optimization, and classification evaluation.