QRNG-DD is an open-source research infrastructure for securely distributing quantum random numbers across network boundaries. The system implements a software-based data diode architecture that allows researchers to access quantum randomness from protected internal networks while maintaining strict security isolation. We designed QRNG-DD to support quantum computing experiments, cryptographic studies, and the emerging paradigm of AI-assisted research workflows. Our Rust implementation achieves high-performance entropy delivery with throughput limited by QRNG hardware rather than software overhead. Multi-source entropy aggregation using XOR or HKDF (HMAC-based Key Derivation Function) mixing defends against single-vendor failures and potential backdoors. The Model Context Protocol (MCP) integration allows AI agents to consume quantum randomness through standardized tools, supporting autonomous scientific workflows in quantum computing, machine learning, and computational physics. |The system addresses key research challenges: transparent entropy distribution for reproducible studies, AI-accessible quantum randomness for autonomous research agents, high-throughput delivery for Monte Carlo simulations, and affordable deployment for academic institutions. All source code and benchmark artifacts are available under MIT license.
Valer Bocan (Mon,) studied this question.