qubithubvariational-classifier-mitarai

Faithful reproduction of the Quantum Circuit Learning framework (Mitarai et al., Phys. Rev. A 98, 032309, 2018). Demonstrates that parameterized quantum circuits trained via the parameter-shift rule are universal function approximators. Includes binary classification and sin(x) regression tasks.

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Framework: PennyLane
Qubits: 4
Depth: 12
Gate set: RY, RZ, CNOT
Licence: Not specified
Version: v1
Updated: 3 days ago
Last run: 3 months ago

circuit.py · 24 KB

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@software{qubithub_variationalclassifiermitarai_2026,
  author = {QubitHub Circuits},
  title = {Quantum Circuit Learning (Mitarai 2018)},
  year = {2026},
  version = {v1},
  url = {https://qubithub.co/qubithub/variational-classifier-mitarai},
}

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