unitary_infidelity

Graph.unitary_infidelity(unitary_operator, target, *, name=None)

Calculate the infidelity between a target operation and the actual implemented unitary.

Both operators must be square and have shapes broadcastable to each other.

Parameters

• unitary_operator (np.ndarray or Tensor) – The actual unitary operator, $U$, with shape (..., D, D). Its last two dimensions must be equal and the same as target, and its batch dimensions, if any, must be broadcastable with target.
• target (np.ndarray or Tensor) – The target operation with respect to which the infidelity will be calculated, $V$, with shape (..., D, D). Its last two dimensions must be equal and the same as unitary_operator, and its batch dimensions, if any, must be broadcastable with unitary_operator.
• name (str or None , optional) – The name of the node.

Returns

The infidelity between the two operators, with shape (...).

Return type

Tensor

SEE ALSO

Graph.density_matrix_infidelity : Infidelity between two density matrices.

Graph.infidelity_pwc : Total infidelity of a system with a piecewise-constant Hamiltonian.

Graph.infidelity_stf : Total infidelity of a system with a sampleable Hamiltonian.

Graph.state_infidelity : Infidelity between two quantum states.

Notes

The operational infidelity between the actual unitary and target operators is defined as

Examples

Calculate the infidelity of a unitary with respect to a $\sigma_x$ gate.

>>> theta = 0.5
>>> sigma_x = np.array([[0, 1], [1, 0]])
>>> unitary = np.array([[np.cos(theta), np.sin(theta)], [np.sin(theta), -np.cos(theta)]])
>>> graph.unitary_infidelity(unitary_operator=unitary, target=sigma_x, name="infidelity")
<Tensor: name="infidelity", operation_name="unitary_infidelity", shape=()>
>>> result = bo.execute_graph(graph=graph, output_node_names="infidelity")
>>> result["output"]["infidelity"]["value"]
0.7701511529340699

Calculate the time-dependent infidelity of the identity gate for a noiseless single qubit.

>>> sigma_x = np.array([[0, 1], [1, 0]])
>>> hamiltonian = sigma_x * graph.pwc_signal(
...     duration=1, values=np.pi * np.array([0.25, 1, 0.25])
... )
>>> unitaries = graph.time_evolution_operators_pwc(
...     hamiltonian=hamiltonian, sample_times=np.linspace(0, 1, 10)
... )
>>> graph.unitary_infidelity(
...     unitary_operator=unitaries, target=np.eye(2), name="infidelities"
... )
<Tensor: name="infidelities", operation_name="unitary_infidelity", shape=(10,)>
>>> result = bo.execute_graph(graph=graph, output_node_names="infidelities")
>>> result["output"]["infidelities"]["value"]
array([0.        , 0.00759612, 0.03015369, 0.0669873 , 0.32898993,
       0.67101007, 0.9330127 , 0.96984631, 0.99240388, 1.        ])