uniqc.algorithms.core.training package

Submodules

• uniqc.algorithms.core.training.hybrid_model module
  • HybridQCLModel
    • HybridQCLModel.forward()
• uniqc.algorithms.core.training.qaoa_torch module
  • QAOASolver
    • QAOASolver.solve()
    • QAOASolver.step()
  • build_maxcut_hamiltonian()
  • build_qaoa_circuit()
• uniqc.algorithms.core.training.qcnn module
  • QCNNClassifier
    • QCNNClassifier.forward()
• uniqc.algorithms.core.training.qnn module
  • QNNClassifier
    • QNNClassifier.forward()
• uniqc.algorithms.core.training.vqe_torch module
  • VQESolver
    • VQESolver.solve()
    • VQESolver.step()
  • build_h2_hamiltonian()
  • build_hea_circuit()

Module contents

Variational quantum algorithm training modules.

Provides reusable algorithm implementations using TorchQuantum backend for native PyTorch autograd-based optimization.

Requires the optional dependencies installed by unified-quantum[pytorch].