Policy-controlled NVIDIA CUDA-Q execution with resource preflight, target guardrails, diagnostics, backend comparison, and tamper-evident audit trails.
A collection of Python samples demonstrating how to get started with IonQ using various quantum frameworks
Quantum-native deep-learning layers that slot directly into PyTorch and run on NVIDIA CUDA-Q simulators or real QPUs.
OpenQASM VS Code Extension
CUDA-Q-compatible Apple Silicon simulator fork with MKL-Q targets
AI-driven generative quantum circuit design for molecular & materials discovery — GNN + Transformer + QD-GRPO reinforcement learning + CUDA-Q, validated on QPU hardware. GIC 2026.
Qute is a testing harness for Quantum simulation applied to threat informed anomaly detections.
Lightweight resource-aware quantum development platform for expectation-based NISQ workloads across CPU, CUDA-Q/GPU, and IBM Quantum.
Ramanujan's mathematics meets the NVIDIA stack: CUDA-Q/cuQuantum quantum simulation + NIM/Nemotron analysis, consumer RTX to cloud H100
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