qml.qinfo.transforms.reduced_dm

reduced_dm(tape, wires, **kwargs)

Compute the reduced density matrix from a QNode returning state().

Warning

The qml.qinfo.reduced_dm transform is deprecated and will be removed in v0.40. Instead, include the pennylane.density_matrix() measurement process in the return line of your QNode.

Parameters

• tape (QuantumTape or QNode or Callable)) – A quantum circuit returning state().

• wires (Sequence(int)) – List of wires in the considered subsystem.

Returns

The transformed circuit as described in qml.transform. Executing this circuit will provide the reduced density matrix in the form of a tensor.

Return type

qnode (QNode) or quantum function (Callable) or tuple[List[QuantumTape], function]

Example

import numpy as np

dev = qml.device("default.qubit", wires=2)

@qml.qnode(dev)
def circuit(x):
    qml.IsingXX(x, wires=[0,1])
    return qml.state()

>>> transformed_circuit = reduced_dm(circuit, wires=[0])
>>> transformed_circuit(np.pi/2)
tensor([[0.5+0.j, 0. +0.j],
        [0. +0.j, 0.5+0.j]], requires_grad=True)

This is equivalent to the state of the wire 0 after measuring the wire 1:

@qml.qnode(dev)
def measured_circuit(x):
    qml.IsingXX(x, wires=[0,1])
    m = qml.measure(1)
    return qml.density_matrix(wires=[0]), qml.probs(op=m)

>>> dm, probs = measured_circuit(np.pi/2)
>>> dm
tensor([[0.5+0.j, 0. +0.j],
        [0. +0.j, 0.5+0.j]], requires_grad=True)
>>> probs
tensor([0.5, 0.5], requires_grad=True)

See also

pennylane.density_matrix() and pennylane.math.reduce_dm()

code/api/pennylane.qinfo.transforms.reduced_dm

 

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