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Xanadu Releases PennyLane, the First Dedicated Machine Learning Software for Quantum Computers



Envisioned as the "TensorFlow of quantum computing," hardware-agnostic PennyLane comes with built-in support for existing qubit and photonic quantum hardware.


Press release from Xanadu
November 13th 2018 | 400 readers

Xanadu Releases PennyLane, the First Dedicated Machine Learning Software for Quantum Computers
Xanadu, a leader in photonic quantum computing and advanced artificial intelligence, today announced PennyLane, the first dedicated machine learning software for quantum computers. Free and open source, PennyLane will enable programmers, researchers, and enthusiasts worldwide to take part in the cutting-edge field of quantum machine learning - the next big step for AI. The software can integrate seamlessly with currently available APIs and quantum hardware from the biggest players in the field.

"Deep learning libraries like TensorFlow and PyTorch opened up artificial intelligence to the world by providing an interface to powerful GPU hardware. With PennyLane, Xanadu is now doing the same for machine learning on quantum hardware," said Seth Lloyd, Xanadu's chief scientific advisor, MIT professor and a founding figure in both quantum computing and quantum machine learning. "We're going to see an explosion of ideas, now that everyone can train quantum computers like they would train deep neural networks."

Xanadu is already a demonstrated industry leader in bringing machine learning and quantum computing together. Their Strawberry Fields software stack, released earlier this year, was the first quantum software to incorporate a simulator built with the machine learning library TensorFlow. This enabled the rapid prototyping and optimization of quantum circuits using existing machine learning tools.

Recognizing the need to also implement machine learning algorithms, which can scale as quantum computers grow in size, Xanadu created PennyLane from the ground up, envisioning it as the "TensorFlow of quantum computing." Under the hood, PennyLane's core feature is that it implements a version of the backpropagation algorithm - the workhorse for training deep learning models - that is naturally compatible with quantum devices.

As quantum computers grow more powerful, and as new vendors make their quantum hardware available over the next few years, PennyLane will integrate seamlessly. Thanks to a plugin system, PennyLane is able to interact with quantum computers from different companies (such as the IBM Quantum Experience) in a hardware-agnostic way. It can even combine quantum subroutines from different hardware together into a larger hybrid computation.

"We're really thrilled to introduce PennyLane to the world," said Nathan Killoran, head of development for PennyLane. "Even with ongoing intense R&D from groups at Xanadu and elsewhere, quantum machine learning is still a largely unexplored, fertile territory. By building a community around a common software platform, we will accelerate innovation in this exciting and important field."


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