qubithubquantum-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.

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Framework: PennyLane
Qubits: 4
Depth: 8
Gate set: RZ, RY, CX
Licence: Not specified
Version: v1
Updated: 3 days ago
Last run: 3 months ago

README.md · 9.1 KB

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@software{qubithub_quantumkernelsvm_2026,
  author = {QubitHub Circuits},
  title = {Quantum Kernel SVM},
  year = {2026},
  version = {v1},
  url = {https://qubithub.co/qubithub/quantum-kernel-svm},
}

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