CUDA-QX

CUDA-QX is a collection of libraries that build upon the CUDA-Q programming model to enable the rapid development of hybrid quantum-classical application code leveraging state-of-the-art CPUs, GPUs, and QPUs. It provides a collection of C++ libraries and Python packages that enable research, development, and application creation for use cases in quantum error correction and hybrid quantum-classical solvers.

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You can read more about CUDA-QX in the release blog and see code examples in the CUDA-QX documentation.

CUDA-Q Solvers

The CUDA-Q Solvers library provides high-level quantum-classical hybrid algorithms and supporting infrastructure for quantum chemistry and optimization problems. It features implementations of VQE, ADAPT-VQE, and supporting utilities for Hamiltonian generation and operator pool management.

Learn more in the CUDA-Q Solvers documentation and explore a number of detailed examples.

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CUDA-Q QEC

The CUDA-Q QEC library provides a comprehensive framework for quantum error correction research and development.

Learn more in the CUDA-Q QEC documentation and explore a number of detailed examples.

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