CUDA-Q Guide Purpose Guide users through CUDA-Q installation, basic kernels, GPU simulation targets, QPU access, built-in applications, multi-GPU execution, and Python authoring. For Qiskit-to-CUDA-Q ports, route to the skill instead. Prerequisites - Python 3.10+ for Python CUDA-Q workflows. - CUDA Toolkit and an NVIDIA GPU for GPU-accelerated targets on Linux. - CPU-only simulation is available through ; macOS is CPU-only. - C++ workflows require Linux or WSL and C++20. - QPU workflows require provider-specific credentials and accounts. Instructions - Invoke with . - If no argument is given,…