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Add TECS-L: Number Theory Meets Neural Architecture#156

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dancinlife:add-tecs-l
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Add TECS-L: Number Theory Meets Neural Architecture#156
dancinlife wants to merge 1 commit intorossant:masterfrom
dancinlife:add-tecs-l

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Summary

  • Adds TECS-L to the Number Theory section
  • TECS-L is a mathematical framework connecting number theory (divisor functions, Euler's totient) to neural network Mixture-of-Experts architecture
  • Key result: proves σ(n)φ(n) = nτ(n) iff n=6, and derives optimal inhibition ratio I≈1/e for MoE models
  • Includes 194 hypotheses with formal proofs

The project is freely available on GitHub and fits naturally alongside existing number theory resources.

Add TECS-L to the Number Theory section - a mathematical framework
that connects divisor functions to neural network MoE architecture,
proving optimal inhibition ratio I≈1/e.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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