Getting started

Once the PennyLane-Qiskit plugin is installed, the three provided Qiskit devices can be accessed straightaway in PennyLane.

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

import pennylane as qml
dev = qml.device('qiskit.aer', 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)

You can also change the default device’s backend with

dev = qml.device('qiskit.aer', wires=2, backend='unitary_simulator')

To get a current overview what backends are available you can query this by

dev.capabilities()['backend']

While the device 'qiskit.aer' is the standard go-to simulator that is provided along the Qiskit main package installation, there exists a natively included python simulator that is slower but will work usually without the need to check out other dependencies (gcc, blas and so on) which can be used by 'qiskit.basicaer'.

Another important difference between the two is that while 'qiskit.aer' supports a simulation with noise, 'qiskit.basicaer' does not.

Noise models

You can instantiate a noise model and apply it to the device by calling

import pennylane as qml

import qiskit
from qiskit.providers.aer.noise.device import basic_device_noise_model

qiskit.IBMQ.load_account()
provider = qiskit.IBMQ.get_provider(group='open')
ibmq_16_melbourne = provider.get_backend('ibmq_16_melbourne')
device_properties = ibmq_16_melbourne.properties()

noise_model = basic_device_noise_model(device_properties)

dev = qml.device('qiskit.aer', wires=2, noise_model=noise_model)

Please refer to the Qiskit documentation for more information on noise models.

IBM Q Experience

PennyLane-Qiskit supports running PennyLane on IBM Q hardware via the qistkit.ibmq device. You can choose between different backends - either simulators or real hardware.

import pennylane as qml
dev = qml.device('qiskit.ibmq', wires=2, backend='ibmq_16_melbourne')

By default, the qiskit.ibmq device will attempt to use an already active or stored IBM Q account. If none are available, you may also directly pass your IBM Q API token, as well as an optional URL:

import pennylane as qml
dev = qml.device('qiskit.ibmq', wires=2, backend='ibmq_qasm_simulator', ibmqx_token="XXX")

In order to avoid accidentally publishing your token, it is best to store it using the qiskit.IBMQ.save_account() function. Alternatively, you can specify the token or URL via the PennyLane configuration file by adding a section such as

[qiskit.global]

  [qiskit.ibmq]
  ibmqx_token = "XXX"
  ibmqx_url = "XXX"

Note that, by default, the qiskit.ibmq device uses the simulator backend ibmq_qasm_simulator, but this may be changed to any of the real backends as given by

dev.capabilities()['backend']