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allaun
b6a4cf9e4d
Density now measured by information-theoretic bounds, not just counts: Shannon entropy H = -Σ p(x) log₂ p(x) over equation symbol distribution - Higher H = more informational diversity = denser content - RG flow bound: H < ln(2⁸) ≈ 2.08 for 8-strand representation Landauer cost E = N·kT·ln(2) where N = distinct math tokens - Each distinct symbol requires erasing energy - kT = 0.025 eV at 290K → ~0.017 eV per bit Density levels: THERMODYNAMIC_SATURATION: both Shannon + Landauer exceed bounds SHANNON_SATURATED: entropy > rgflow fixed-point LANDAUER_EXPENSIVE: energy cost too high COUNT_EXCEEDED: simple count threshold |
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| avm | ||
| bin | ||
| nuvmap | ||
| pist | ||
| q16 | ||
| silversight | ||
| lib.rs | ||