to_pennylane#
- discopy.quantum.pennylane.to_pennylane(disco_circuit, probabilities=False, backend_config=None, diff_method='best')[source]#
Return a PennyLaneCircuit equivalent to the input DisCoPy circuit. probabilties determines whether the PennyLaneCircuit returns states (as in DisCoPy), or probabilties (to be more compatible with automatic differentiation in PennyLane).
- Parameters:
disco_circuit (
discopy.quantum.circuit.Circuit
) – The DisCoPy circuit to convert to PennyLane.probabilities (bool, default: False) – Determines whether the PennyLane circuit outputs states or un-normalized probabilities. Probabilities can be used with more PennyLane backpropagation methods.
backend_config (dict, default: None) – A dictionary of PennyLane backend configration options, including the provider (e.g. IBM or Honeywell), the device, the number of shots, etc. See the PennyLane plugin documentation for more details.
diff_method (str, default: "best") – The differentiation method to use to obtain gradients for the PennyLane circuit. Some gradient methods are only compatible with simulated circuits. See the PennyLane documentation for more details.
- Returns:
The PennyLane circuit equivalent to the input DisCoPy circuit.
- Return type: