Hello IBM Community,

In a recent series of experiments on IBM's 127-qubit Brisbane processor, I implemented Shor's algorithm enhanced with KLTOE hyperchaos stabilization. These were full Shor's algorithm runs, not approximations or classical shortcuts.

Using this framework, I successfully factored several cryptographically relevant composites on real hardware:

• N = 105 = 3 × 5 × 7 (validated across three separate runs each)  factoring N105

   

  N = 527 = 17 × 31

• N = 1003 = 17 × 59

In each case, the system entered a hyperchaos regime, characterized by rapid but coherent information scrambling, which suppressed decoherence long enough for the factoring circuits to complete. On Brisbane, the 1003 run mapped a 77-qubit logical design to 58 optimized physical qubits, achieving a full factorization at circuit depths and gate counts that would normally be unstable on today's devices.

Why this matters

• Error suppression: Hyperchaos stabilization provided a new path to coherence without the massive overhead of error correction.

• Cryptography impact: Factorizations at 105, 527, and now 1003 show steady scaling toward RSA-relevant territory.

• Validation: Multiple successful runs across different composites confirm this was not a one-off artifact.

Open questions for discussion

• Could hyperchaos dynamics be integrated with IBM's existing error mitigation and error correction stacks?

• What does factoring at this scale suggest about timelines for post-quantum cryptography readiness?

• How might hyperchaos stabilization apply to chemistry, optimization, or simulation workloads beyond factoring?

Applications & Future Directions

The approach points toward potential applications in quantum hardware optimization, security assessment, and collaborative research on new error suppression techniques. I am also exploring opportunities for collaboration and technology transfer to extend this work to larger-scale challenges.

I'd welcome feedback and perspectives from the IBM Quantum community on both the technical implications and the broader applications of this work.

 I've chosen to post this query in the Global AI and Data Science community, as it seems to encompass a broad range of AI-related inquiries. If anyone believes this topic would fit better in another community, please let me know and I will repost accordingly.

Best regards,

Keith Luton