paddle_quantum.backend.quleaf

The source file of the quleaf backend.

paddle_quantum.backend.quleaf.set_quleaf_backend(backend)

Set the backend of the QuLeaf.

Parameters:

backend (str) – The backend you want to set.

paddle_quantum.backend.quleaf.get_quleaf_backend()

Get the current backend of the QuLeaf.

Returns:

Current backend of the QuLeaf.

Return type:

str

paddle_quantum.backend.quleaf.set_quleaf_token(token)

Set the token of the QuLeaf.

You need to input your token if you want tu use the cloud server.

Parameters:

token (str) – Your token.

paddle_quantum.backend.quleaf.get_quleaf_token()

Get the token you set.

Returns:

The token you set.

Return type:

str

class paddle_quantum.backend.quleaf.ExpecValOp

Bases: PyLayer

static forward(ctx, state, hamiltonian, shots, *parameters)

The forward function to compute the expectation value of the observable in the QuLeaf Backend.

Parameters:

  • ctx (PyLayerContext) – To save some variables so that they can be used in the backward function.

  • param – The parameters in the previous quantum gates.

  • state (State) – The quantum state to be measured.

  • hamiltonian (Hamiltonian) – The observable.

  • shots (Tensor) – The number of measurement shots.

  • *parameters – The parameters in the parameterized quantum circuit.

Returns:

The expectation value of the observable for the input state.

Return type:

Tensor

static backward(ctx, expec_val_grad)

The backward function which is to compute the gradient of the input parameters.

Parameters:

  • ctx (PyLayerContext) – To get the variables saved in the forward function.

  • expec_val_grad (Tensor) – The gradient of the expectation value.

Returns:

The gradient of the parameters for the quantum gates.

Return type:

Tensor