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ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Boundary Conditions on Mathematical Emergence: A TAME Framework Analysis of Factorization Domains

Authors: Sweder Gold, David;

Boundary Conditions on Mathematical Emergence: A TAME Framework Analysis of Factorization Domains

Abstract

Michael Levin's Technological Approach to Mind Everywhere (TAME) framework proposes that cognitive-like properties emerge in systems satisfying three structural conditions: degrees of freedom in component states, cascading consequences of local decisions, and collective resolution of ambiguity. We apply this framework to a novel domain — pure mathematics — by analyzing factorization in algebraic number rings. We prove that the standard integers (ℤ) cannot satisfy TAME's structural prerequisites due to unique factorization, establishing a rigorous boundary condition. We then demonstrate that rings of algebraic integers with non-unique factorization (ℤ[√d] for appropriate d) satisfy all three conditions: ~14% of norms exhibit intrinsic factorization ambiguity, single factorization choices cascade through 90%+ of the network, and agent-based negotiation produces robust collective consensus (Jaccard similarity 0.98–1.00 vs. 0.37–0.42 null). Agents collectively discover the splitting behavior of primes — a fundamental concept in algebraic number theory — through purely local interaction, with split-fine alignment improving +0.10 to +0.31 over null across all tested class numbers (h = 2 through 5). Perturbation experiments reveal that this collective pattern functions as a robust attractor: even complete randomization of agent beliefs results in 98–100% recovery, with the algebraic signal perfectly preserved. These results suggest that the boundary between unique and non-unique factorization domains constitutes a mathematically precise analog to the boundary between systems with and without emergent collective computation.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average