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.

Run Cite

No licence specified, so all rights are reserved by default — forking copies this circuit but grants you no rights to reuse it.

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

qubithub.toml · 388 B

Lineage

Not a fork.

No forks yet.

Suggested citation

@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},
}

Generated from this circuit's metadata. QubitHub does not mint DOIs, so this is not a registered identifier — check it against your venue's requirements before publishing.

Code

Lineage

Suggested citation