Shipped: Quantum AI and Cryptanalysis on Real IBM Quantum Hardware

An open-source quantum computing research proof of concept investigating quantum cryptanalysis and quantum machine learning using IBM's quantum computing ecosystem.

The project combines educational demonstrations of Shor's algorithm for small-number factorization with Quantum Neural Network (QNN) training and evaluation.

Experiments include quantum circuit construction, measurement analysis, classical post-processing, and QNN classification performance on real quantum hardware.

The repository documents practical challenges associated with current noisy quantum systems, including unstable training, limited classification accuracy, and quantum hardware constraints.

The experiments demonstrate the difference between idealized quantum algorithms and practical implementations using available quantum computing resources.

Designed for AI researchers, quantum developers, cybersecurity professionals, and educators exploring quantum machine learning and the future implications of quantum computing for cryptography.

The factorization examples use small educational values and do not demonstrate the ability to break production RSA encryption.