Announcing the Xanadu Quantum Software Competition

Encouraging the use of quantum software across three areas: education, software development, and research — with multiple prizes of up to $1000 on offer.

Interested in quantum computing and quantum software, and want to use the latest quantum hardware? Have a cool idea for an educational YouTube video, Jupyter Notebook, research paper, or just itching to get your hands dirty with Strawberry Fields or PennyLane?

We’re excited to announce the Xanadu Quantum Software Competition, open to everyone — with prizes of $1000 for first place finishers.

The Xanadu Quantum Software Competition consists of three awards:

  1. Education award (for those who enjoy teaching and scientific communication),
  2. Software award (for those who enjoy tinkering with the cutting-edge of physics and technology), and
  3. Research award (for those who love pushing the boundaries of knowledge).

All categories include a first place prize of CAD$1000, and a second place prize of CAD$500, with finalists profiled on Xanadu’s social media and blog.

The entry deadline for all three awards is 30th August 2019 — plenty of time to get those creative juices flowing.

To submit your entries, go to https://pennylane.ai/competition.


About our software

PennyLane is the first dedicated library for quantum machine learning, leveraging actual quantum hardware to calculate gradients and perform machine learning and optimization. It can be used to apply well-known algorithms such as quantum approximate optimization algorithms (QAOA), variational quantum eigensolvers (VQE), quantum classifiers, quantum generative adversarial networks (QGANs), quantum neural networks (QNN), and many other hybrid quantum-classical models.

Not only that, but PennyLane allows you to run these machine learning algorithms directly on existing quantum hardware platforms — with plugins existing for Project Q, Qiskit (supporting the IBM Q hardware backend), and Strawberry Fields; with a Rigetti Forrest plugin coming soon.

Strawberry Fields, meanwhile, is a full-stack quantum software platform for photonic quantum computing, and ideal for quantum neural networks. Using its built-in suite of quantum simulators — implemented using NumPy and Tensorflow — allows full classical optimization and machine learning techniques to be applied to photonic quantum computation.


What are we looking for?

Almost anything! Your creativity is the limit.

If you love explaining and communicating topics in quantum computation, your submission could be in any form you feel best demonstrates and highlights an interesting phenomena in quantum computation using Strawberry Fields or PennyLane. This includes posters, Jupyter notebooks, a children’s book, a video, or even an animation.

Have a passion for machine learning, and getting curious about quantum machine learning? Send us a cool application that takes advantage of PennyLane’s automatic differentiation on near-term quantum hardware.

Or, if you’re involved in quantum information and quantum machine learning research, submit a link to your publicly listed preprint or published paper that uses Strawberry Fields or PennyLane, and you will be in the running for a cool $1000.

For some ideas to stimulate the brain, check out the PennyLane and Strawberry Fields documentation, read our whitepapers, play around with Strawberry Fields Interactive, and see what other cool things people have done in the Strawberry Fields Gallery and the PennyLane examples.

And don’t forget to submit!


We’re entering an exciting time in quantum physics and quantum computation: near-term quantum devices are rapidly becoming a reality, accessible to everyone over the Internet. This, in turn, is driving the development of quantum software — we need a way to program and simulate these quantum devices.

We can’t wait to see your submissions. For the terms and conditions and general competition rules, please see here.