🏎️ CUDA-Q

To do algorithm research and build applications for future quantum advantages, a bridging technology is needed to enable dynamic workflows across disparate system architectures.

With a unified and open programming model, NVIDIA CUDA-Q is an open-source platform for integrating and programming quantum processing units (QPUs), GPUs, and CPUs in one system. CUDA-Q enables GPU-accelerated system scalability and performance across heterogeneous QPU, CPU, GPU, and emulated quantum system elements.

CUDA-Q is a programming model and toolchain available in C++ and Python.

Learn more: Check out CUDA-Q documentation, examples and applications.

Participate: Explore the code in our repository and contribute.

Open bounties:

• $100 | Enable emitting circuit diagrams for unitary quantum kernels in LaTeX
• $100 | Organize Documentation Examples
• $100 | State Preparation Circuit Synthesis via Matrix Product State Decomposition
• $75 | Dynamic support of QPU topologies for the mapping pass
• $75 | Readout Error Mitigation
• $50 | Bloch sphere visualization for single-qubit operations