April 11, 2018
Here at Xanadu, we have some of the brightest minds tackling the problem of practical quantum computation. As a full-stack quantum startup, we take a three-pronged approach to quantum computing:
- Hardware: Our experimental physicists are working around the clock to develop an on-chip quantum photonic processor. Stay tuned — we’ll have some exciting news to share soon.
- Applications and algorithms: Our algorithms team has already started publishing results across diverse fields such as quantum chemistry, graph theory, machine learning and more, while simultaneously making advances in photonic quantum computing. Check out our recent papers if you haven’t already.
- Software and simulations: Underpinning the work of our algorithms team is the ability to easily simulate our quantum photonics system. This is a hugely important component, allowing us to quickly flesh out ideas, and discover and probe interesting and unexpected behaviour.
As part of these efforts, we have developed a full stack software solution for simulating quantum photonics and continuous variable quantum computing. And that’s not all — we have also integrated support for Tensorflow, creating a framework that combines the latest advances in deep learning and machine learning with quantum computation.
The best part? Our framework is now open-sourced and available for anyone to use and play with.
Introducing Strawberry Fields and Blackbird.
An open-source full-stack quantum software platform for photonic quantum computing.
- Implemented in Python for ease-of-use, Strawberry Fields is specifically targeted to continuous-variable quantum computation. Quantum circuits are written using the easy-to-use and intuitive Blackbird quantum programming language.
- Powers the Strawberry Fields Interactive web app, which allows anyone to run a quantum computing simulation via drag and drop. Quantum computing has never been simpler.
- Includes a suite of quantum simulators implemented using NumPy and Tensorflow — these convert and optimize Blackbird code for classical simulation.
- Future releases will target experimental backends, including photonic quantum computing chips.
These last two features are the most thrilling to us here at Xanadu. Not only is Strawberry Fields the first quantum computing simulator to include gradient-based optimization of quantum circuits — designed to be intuitive even without a background in machine learning — soon, you’ll be able to run quantum experiments directly on our quantum photonics chip.
Simulation and physical experiments: all from the same piece of code.
What can I use it for?
Whatever you like! The sky is the limit.
Pushing the theoretical limits of quantum computation
Strawberry Fields is ideal for studying existing algorithms, or quickly prototyping new ideas and breakthroughs.
Designing and prototyping quantum photonics
Need to design a photonics experiment before committing to buying expensive components? Perhaps you’d like to optimize a photonics set-up, to make maximum use of the components you already have available.
Exploration and design of novel quantum circuits
On the other hand, do you know the output you need, but you’re not sure how exactly to get there? Exploit the built-in Tensorflow support and use deep learning to design and optimize circuits.
If you find yourself in a situation where you need additional features for your research, get in touch with us — Strawberry Fields is still under heavy development, and we are always open to hearing how we can make it a more integral part of your research workflow.
Okay, you’ve convinced me. How do I start?
To see Strawberry Fields in action immediately, try out our Strawberry Fields Interactive web application. Prepare your initial states, drag and drop gates, and watch your simulation run in real time right in your web browser.
To take full advantage of Strawberry Fields, however, you’ll want to use the Python library. The best place to start is our documentation — we have put together an extensive selection of pages discussing continuous-variable quantum theory, quantum algorithms, and of course installation instructions and details of the Strawberry Fields API. This is supplemented by an array of tutorials; starting from the introductory (a basic guide to quantum teleportation) to the more advanced (machine learning and gradient-based optimization of quantum circuits).
You can also check out the source code directly on GitHub — the issue tracker is a great place to leave any feedback or bug reports. Alternatively, if you’d like to contribute directly, simply fork the repository and make a detailed pull request.
For more technical details regarding the Strawberry Fields architecture, be sure to read our whitepaper.
It is difficult to overstate just how excited we are. Strawberry Fields is the accumulation of months of hard work, and gives us the chance to share our progress with the quantum computing community.
But this is just the start — we have a ton of exciting projects in the pipeline. Watch this space.