Basics

Begin your journey into PennyLane and Quantum Machine Learning (QML) by exploring the tutorials below.

The Getting started section is a great place to start if you’ve just discovered PennyLane and QML and want to learn more about the basics. Or venture straight into the Applications section and explore how to implement trainable circuits for popular applications such as Variational Quantum Eigensolvers and Quantum Chemistry, using either simulators or near-term quantum hardware.

Getting started

Here you can discover the basic tools needed to use PennyLane through simple demonstrations. Learn about training a circuit to rotate a qubit, machine learning tools to optimize quantum circuits, and introductory examples of photonic quantum computing.

Applications

Get familiar with more advanced applications of PennyLane and quantum machine learning in this section. Learn how to implement a variational quantum eigensolver, play around with quantum chemistry simulations, solve graph problems such as MaxCut, or implement quantum machine learning circuits on real near-term hardware.

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