PennyLane-Orquestra Plugin

Release

0.33.0

Warning

This plugin will not be supported in newer versions of PennyLane. It is compatible with versions of PennyLane up to and including 0.33.

The PennyLane-Orquestra plugin integrates the Orquestra workflow management system for quantum computing with PennyLane’s quantum machine learning capabilities.

PennyLane is a cross-platform Python library for differentiable programming of quantum computers.

Orquestra is a workflow management system for quantum computing.

Once the PennyLane-Orquestra plugin is installed, multiple devices offered by Orquestra can be accessed straightaway in PennyLane, without the need to import new packages.

Devices

There are four different devices available:

'orquestra.forest'

Integration with Rigetti Forest devices.

'orquestra.ibmq'

Integration with Qiskit remote hardware and simulators.

'orquestra.qiskit'

Integration with Qiskit simulator backends.

'orquestra.qulacs'

Integration with the Qulacs simulator.

For example, the 'orquestra.qiskit' device with two wires is called like this:

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

Device options

The devices provided by the PennyLane-Orquestra plugin accept additional arguments beyond the PennyLane default device arguments. These are added to a base OrquestraDevice class.

backend=None

The Orquestra backend device to use for the specific Orquestra backend, if applicable (e.g., 'statevector_simulator' for 'orquestra.qiskit')

batch_size=10

The size of each circuit batch when using the batch_execute() method to send multiple workflows.

keep_files=False

Whether or not the workflow files generated during the circuit execution should be kept or deleted.

resources=None

An option for Orquestra, specifies the resources to be specified for each workflow step.

timeout=600

The time until a job should timeout after getting no response from Orquestra (in seconds).

index

 

Download Python script

 

Download Notebook

 

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