This repo contains CUDA-Q Academic materials, including self-paced Jupyter notebook modules for building and optimizing hybrid quantum-classical algorithms using CUDA-Q.

Prototype hybrid classical-quantum workflow aligned with NVIDIA quantum-GPU news. Includes a policy gate for AI safety and security, uses a Qiskit simulator backend, emits JSON for audit, and can be extended to CUDA-Q or neutral-atom or photonic hardware.

OpenQASM VS Code Extension

Minicurso de quantum Machine learning

Rust HAL for quantum hardware. One Python API across IBM, IQM, Quantinuum, AQT, IonQ, Quandela, Scaleway, AWS Braket, NVIDIA CUDA-Q, MQT DDSIM and a local simulator, with Qiskit / Cirq / Qrisp / PennyLane as input converters.

Quantum Measurement–Driven Security Lab (QKD + ODMR + QML)

Bare-metal performance engineer — hand-written CUDA/Rust/C++ for physics, quantum & neuro. Benchmarks I can defend.

Quantum portfolio optimisation: NVIDIA Ising + CUDA-Q + Claude AI. 373x GPU speedup · +3.1% vs classical · 1.4M× sampling efficiency · QPU validated on Rigetti Cepheus-1-108Q.

CUDA-Q Experiments

AI-driven generative quantum circuit design for molecular & materials discovery — GNN + Transformer + QD-GRPO reinforcement learning + CUDA-Q, validated on QPU hardware. GIC 2026.

VQE ground-state solver for the Jaynes-Cummings quantum optics model, built with NVIDIA CUDA-Q