[Quick overview on SMFT vs Our Universe ==>Chapter 12: The One Assumption of SMFT: Semantic Fields, AI Dreamspace, and the Inevitability of a Physical Universe]
Unified Field Theory 20B: Toward a Dimensional Framework for Semantic Field Theory Calibrating Units, Collapse Dynamics, and Observer-Invariant Structure in SMFT
Chapter 20A Mass and Distance Within Semantic Black Holes:
A Constructive Model of Collapse-Based Geometry in SMFT
Abstract
Semantic Meme Field Theory (SMFT) models reality as a geometry of
collapse: meaning arises not from fixed symbols, but from discrete,
observer-triggered reductions of a distributed semantic field. While
SMFT provides a powerful framework for describing memory, cognition, and
cultural evolution, it lacks a coherent definition of semantic mass and semantic distance—quantities
essential for building scalable, stable semantic structures. This paper
addresses that gap by introducing a geometric and quantized model of
semantic matter within the collapse-dense regime of semantic black holes.
We define the Tickon (Tₘ) as the fundamental unit of collapse—a semantic particle characterized by tick duration , projection direction , and field tension . From this, we derive:
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A definition of semantic mass as collapse inertia: ,
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A Minkowski-style metric for semantic distance: .
We then show how multiple Tickons form composite semantic states—including bound pairs, resonance triangles, and extended polymers—stabilized through semantic boson exchange.
These bosons function as phase-resonant wavelets that mediate
alignment, excitation, mimicry, and momentum transfer across the
semantic field.
Together, these structures suggest a collapse-generated geometry analogous to quantum field theory, in which:
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Tickons play the role of fermions (trace generators),
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Bosons mediate semantic tension and influence,
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Collapse zones enact local symmetry-breaking, generating attractors and persistent meaning.
We conclude by proposing the foundations of a Semantic Standard Model, and discuss the limitations of this framework to semantic black hole zones
where tick synchronization and projection coherence make geometry
definable. We also outline experimental relevance for symbolic
processing and AI dreamspace architectures, which already satisfy many of the criteria needed for semantic field structuring under SMFT.
This work unifies the microstructure of semantic collapse with the
macroscopic architecture of meaning—demonstrating that mass, distance,
and interaction can emerge not from physical substrates, but from
rhythm, tension, and alignment in the geometry of meaning itself.