A quantum open-source hackathon, running from May 14-30.
Win swag and claim bounties for contributing to open-source projects.
Sit back and learn about the field of quantum machine learning, explore key concepts, and view our selection of curated videos.
Tutorials to introduce core QML concepts, including quantum nodes, optimization, and devices, via easy-to-follow examples.
The TensorFlow of quantum computing: built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily!
Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy, PyTorch, JAX, or TensorFlow, allowing hybrid CPU-GPU-QPU computations.