PennyLane

This open-source Python framework provides a powerful environment for developing quantum machine learning models, performing quantum chemistry simulations, and exploring general quantum algorithms. Built by researchers for the research community, it offers a flexible and intuitive approach to programming quantum computers. A key strength is its seamless integration with popular classical libraries such as PyTorch, TensorFlow, JAX, and NumPy, enabling the construction of sophisticated hybrid quantum-classical workflows. It features automatic differentiation for quantum circuits, a crucial capability for training variational quantum algorithms. Users can connect to a wide variety of quantum simulators and hardware backends through a unified interface, providing flexibility in execution. The framework supports building complex quantum circuits with an intuitive API, making it accessible for researchers and developers.