Toroidal Manifold Methods for Coherence Enhancement in AI and Physical Quantum Systems: A Technical Disclosure

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Authors: Sylvain Cormier
Cited by: 0

Abstract

Erratum (2026-07-06): the TruthfulQA result cited as "up to +2.8pp" did not survive controlled replication (McNemar p = 0.22; see DOI 10.5281/zenodo.21206458) and should not be cited as an effect. The disclosure's methods and priority dates are unaffected. Defensive technical disclosure establishing prior art for toroidal coherence methods across four domains: AI hallucination reduction via logit bias, quantum dephasing suppression via Tonnetz spectral gap filtering, topological error correction via toric code, and distributed post-quantum attestation. Includes experimental validation on TruthfulQA (4 models, up to +2.8pp improvement) and theoretical framework for room-temperature quantum coherence.

Fields of Study & Subjects

Quantum Computing Algorithms and Architecture Quantum Mechanics and Applications Topic Modeling

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
10 February 2026
Language
EN