# The Numpy-Wavefunction device¶

The rigetti.numpy_wavefunction device provides an interface between PennyLane and the pyQuil NumpyWavefunctionSimulator.

As the NumPy wavefunction simulator allows access and manipulation of the underlying quantum state vector, rigetti.numpy_wavefunction is able to support the full suite of PennyLane and Quil quantum operations and observables.

Note

Since the NumPy wavefunction simulator is written entirely in NumPy, no external Quil compiler is required.

Note

By default, rigetti.numpy_wavefunction is initialized with analytic=True, indicating that the exact analytic expectation value is to be returned.

If the number of trials or shots provided to the rigetti.numpy_wavefunction is instead non-zero, a spectral decomposition is performed and a Bernoulli distribution is constructed and sampled. This allows the rigetti.numpy_wavefunction device to ‘approximate’ the effect of sampling the expectation value.

## Usage¶

You can instantiate the device in PennyLane as follows:

import pennylane as qml

dev_numpy = qml.device('rigetti.numpy_wavefunction', 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 and variance of a measurement and depends on three classical input parameters would look like:

@qml.qnode(dev_numpy)
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(0)), var(qml.PauliZ(1))


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

>>> circuit(0.2, 0.1, 0.3)
array([0.97517033, 0.04904283])


## Supported operations¶

All Rigetti devices support all PennyLane operations and observables, with the exception of the PennyLane StatePrepBase state preparation operations.