MilestoneIndustryConfirmed

Xanadu introduces PennyLane for hybrid quantum programming

Nov 12, 2018

Xanadu researchers introduce PennyLane, a Python framework that combines quantum circuits with classical optimization and machine learning. It computes the gradients used to tune circuit parameters and supports different quantum hardware through plugins.

Why it matters

It gives researchers a common way to build and optimize algorithms that alternate between quantum circuits and conventional computation.

Xanadu

See it on the timeline

IBM releases Qiskit, an open-source toolkit for programming quantum computers (Mar 7, 2017)
Google releases Cirq for programming quantum computers (Jul 18, 2018)

Sources (2)

arXiv (Bergholm et al.) PennyLane: Automatic differentiation of hybrid quantum-classical computations
Primary sourceNov 12, 2018

“PennyLane's core feature is the ability to compute gradients of variational quantum circuits in a way that is compatible with classical techniques such as backpropagation. PennyLane thus extends the automatic differentiation algorithms common in optimization and machine learning to include quantum and hybrid computations. A plugin system makes the framework compatible with any gate-based quantum simulator or hardware.”
PennyLane / Xanadu PennyLane is 5 years old!
Primary sourceNov 21, 2023

“On 12 November 2018, PennyLane had its first moment in the spotlight when it was presented in the paper PennyLane: Automatic differentiation of hybrid quantum-classical computations, as a Python package that seamlessly integrates variational quantum circuit methods as part of hybrid computations.”

Added Oct 28, 2026. Spotted an error? Tell us and we will review it.

Xanadu introduces PennyLane for hybrid quantum programming

Why it matters

Related