Preprint · Release 05

Resonance-Confinement Architecture: A Physically Bounded Substrate for Safe Superintelligence

Richard J. Reyes

Independent Researcher · June 11, 2025 · 10.5281/zenodo.17732661

CategoryAI architecture Research statusControl architecture

Abstract

This architecture proposal maps resonance, coherence, bounded curvature, contradiction control, and Lyapunov-like stabilization into an artificial-intelligence substrate. It is presented as a physically bounded design framework and research specification, not as a completed artificial general intelligence implementation.

Plain-language overview

Research question

Can resonance, coherence, bounded curvature, and Lyapunov-like stabilization be mapped into a physically bounded substrate for artificial intelligence?

Main contribution

  • Maps resonance, coherence, bounded curvature, and contradiction control into an AI substrate design.
  • Specifies Lyapunov-like stabilization as a bounding mechanism.
  • Frames the result as a design framework and research specification.

Evidence type

Conceptual architecture

Current limitations

It is a design framework and research specification, not a completed or evaluated artificial general intelligence implementation.

Research assets

Read & download
Zenodo record (manuscript and files)
Research program hub
geometry_of_resonance — equations, manuscripts, and simulations

Related works

Verification and traceability

This section is generated from the canonical publication traceability registry. Empty fields are reported rather than inferred.

Claim IDs
None registered
Equation IDs
None registered
SymPy audit
None registered
Lean coverage
None registered
Assumptions
None registered
Formalization
ARCHITECTURE_ONLY
Empirical state
NOT_EVALUATED_AS_AGI
Independent replication
NONE_RECORDED
Repositories

Explicit falsifiers

  • A concrete implementation fails its declared stability, contradiction-control, or drift-resistance benchmarks.

Open obligations

  • Publish an executable specification, benchmark suite, ablations, failure modes, and external evaluation.

Recommended citation

Reyes, R. J. (June 11, 2025). Resonance-Confinement Architecture: A Physically Bounded Substrate for Safe Superintelligence. Zenodo. https://doi.org/10.5281/zenodo.17732661

Machine-readable identifiers

DOI
10.5281/zenodo.17732661
Zenodo
https://zenodo.org/records/17732661
Local metadata
https://rickyjreyes.github.io/publications/resonance-confinement-architecture.html
Author
ORCID 0009-0005-5975-8718

This landing page provides accessible summaries and citation metadata for an archival preprint. The authoritative manuscript and downloadable files are maintained on the Zenodo DOI record. Wave Confinement Theory is an evolving independent framework; claims should be evaluated according to the derivations, simulations, experiments, data analyses, assumptions, and limitations stated in the paper itself.