Essay III derives the informational architecture of nothing's structural space from the lattice of Essays I and II. The framework used throughout is pure counting: how many distinct positions exist in a given region of the lattice, and how many bits of binary address are required to distinguish them. No external communication theory, no probabilistic noise model, and no channel-capacity formula is imported. Every result follows from integer arithmetic on the n = 10 discrete lattice and the logarithm function — both of which are structural properties of nothing's lattice, not external impositions. Part I establishes the addressing arithmetic: n = 10 positions per axis require log2 (10) ≈ 3. 32 bits per axis; the full lattice requires ⌈3 × log2 (10) ⌉ = 10 bits to address any position. Part II derives the face-entropy: the maximum entropy of a three-face label is log2 (3) ≈ 1. 585 bits, achieved only in the degenerate uniform partition that T. NE (Essay I) forbids. Part III derives the binary axis-entropies of each axis from its clearance fraction, and establishes the axis-entropy ordering HB > HR > HS — which matches exactly the clearance ordering σ > Λ > Iₘin. Part IV derives each clearance margin's addressing bit-count: Source margin = 1 bit (exactly), Boundary margin = 2 bits (exactly), Remainder margin = log2 (2. 984) ≈ 1. 577 bits (non-integer, sub-lattice). The one-bit step from Source to Boundary is the informational expression of the Unique Combinatorial Lock's c/a = 2 ratio. Part V derives the TSV's informational character: its 336/1000 lattice density gives an information content of log2 (125/42) ≈ 1. 574 bits, which falls precisely one structural bit below log2 (3) — the informational expression of TI exceeding 1/3 by exactly 1/375. Part VI derives the dimensional collapse as information compression: 1/d = 1/3 of the full coordinate information is preserved. Part VII derives the Structural Pixel's information content and the Ontological Shadow's role as the minimum-information 2D clearance cell. Part VIII states the Grand Informational Partition.
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Eugene B. Pretorius (Mon,) studied this question.
www.synapsesocial.com/papers/69df2c2fe4eeef8a2a6b13e1 — DOI: https://doi.org/10.5281/zenodo.19554758
Eugene B. Pretorius
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