qml.devices.qubit.adjoint_jvp¶
-
adjoint_jvp(tape, tangents, state=None)[source]¶ The jacobian vector product used in forward mode calculation of derivatives.
Implements the adjoint method outlined in Jones and Gacon to differentiate an input tape.
After a forward pass, the circuit is reversed by iteratively applying adjoint gates to scan backwards through the circuit.
Note
The adjoint differentiation method has the following restrictions:
Cannot differentiate with respect to observables.
Observable being measured must have a matrix.
- Parameters
tape (QuantumTape) – circuit that the function takes the gradient of
tangents (Tuple[Number]) – gradient vector for input parameters.
state (TensorLike) – the final state of the circuit; if not provided, the final state will be computed by executing the tape
- Returns
gradient vector for output parameters
- Return type
Tuple[Number]