The Spectral Bridge: Unifying Mathematics and Machine Intelligence
Frank Morales Aguilera, BEng, MEng, SMIEEE
The Spectral Bridge: Unifying Mathematics and Machine Intelligence
Frank Morales Aguilera, BEng, MEng, SMIEEE
Chief AI Officer, Drivia Consulting | Founder & CEO, SOMALA | Former Boeing Associate Technical Fellow | Thinkers360 Elite Expert In Open Source, Generative and Agentic AI, AI Governance| Thinkers360 Top Voice 2025
Introduction
For over 160 years, the Riemann Hypothesis has stood as the ultimate fortress of number theory, defying even the most advanced tools of mathematics. Simultaneously, the world of artificial intelligence has grappled with “catastrophic forgetting” — a persistent 37-year-old phenomenon in which neural networks abruptly lose legacy knowledge while acquiring new skills. Though these fields appear disjoint, the **Arithmetic Spectral Theory (AST)** framework reveals they are united by a singular, overlooked mathematical structure: the Pure Kernel of the first six prime numbers. By synthesizing this theory with the legacy of neuroimaging, a constructive resolution to these long-standing challenges emerges.
Method
Results
Discussion
References
- Morales Aguilera, F. (2026). Arithmetic Spectral Theory and TOPO-2026: A Unified Framework Solving the Riemann Hypothesis, Quantifying the Green-Tao Theorem, and Eliminating Catastrophic Forgetting in Artificial Intelligence. Zenodo. https://zenodo.org/records/20805470
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