qubithubvariational-classifier

A parameterized quantum circuit for binary classification — the quantum analogue of a neural network layer. Encodes 2 features into qubit rotations, processes through 2 trainable RY-CX-RZ layers (8 parameters), and measures qubit 0 for class prediction. Achieves >66% accuracy on a 6-sample linearly separable dataset after training.

Run Cite

Framework: Qiskit
Qubits: 2
Depth: 8
Gate set: RY, RZ, CX
Licence: Apache-2.0
Version: v1
Updated: 1 day ago
Runs: None completed

Circuit

circuit.py · Qiskit · depth 8

No completed runs yet.

Runs are private to the person who ran them.

Lineage

Not a fork.

No forks yet.

Suggested citation

@software{qubithub_variationalclassifier_2026,
  author = {QubitHub Circuits},
  title = {Variational Quantum Classifier},
  year = {2026},
  version = {v1},
  url = {https://qubithub.co/qubithub/variational-classifier},
}

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.