# Qiskit device¶

The orquestra.qiskit device provided by the PennyLane-Orquestra plugin allows you to use PennyLane to deploy and run your quantum machine learning models on the backends and simulators provided by Qiskit Aer.

You can instantiate a 'orquestra.qiskit' device for PennyLane with:

import pennylane as qml
dev = qml.device('orquestra.qiskit', wires=2)


This device can then be used just like other devices for the definition and evaluation of QNodes within PennyLane. A simple quantum function that returns the expectation value of a measurement and depends on three classical input parameters would look like:

@qml.qnode(dev)
def circuit(x, y, z):
qml.RZ(z, wires=[0])
qml.RY(y, wires=[0])
qml.RX(x, wires=[0])
qml.CNOT(wires=[0, 1])
return qml.expval(qml.PauliZ(wires=1))


You can then execute the circuit like any other function to get the quantum mechanical expectation value.

circuit(0.2, 0.1, 0.3)


## Backends¶

By default, the orquestra.qiskit device uses the noisy 'qasm_simulator' backend, but this can be changed to 'statevector_simulator'. For more information on backends, please visit the Orquestra interfaces documentation.

You can change an 'orquestra.qiskit' device’s backend with the backend argument when creating the device:

dev = qml.device('orquestra.qiskit', wires=2, backend='statevector_simulator')