The Universal Information Lattice: An Informational Topology Framework for Scale-Invariant Morphogenesis, Multifractal Criticality, and Non-Linear Temporal Trajectories

This preprint introduces the Universal Information Lattice (UIL), a synthetic informational topology framework postulating that four-dimensional spacetime and physical mass distribution are emergent phenomena generated by a sub-quantum thermodynamic matrix. By integrating principles of self-organized criticality (SOC), molecular bioelectricity, and the free-energy principle, the framework establishes a multi-tiered reduction cascade where scale-invariant topological constraints restrict macro-cellular state spaces. Rather than relying on traditional genetic determinism, this model offers a non-chemical, purely geometric mechanism for tissue boundary regulation through gap-junction discontinuities and localized topological frustration. Furthermore, oncological decoupling (cancer) is re-classified as a macrostructural execution error resulting from a localized symmetry collapse from collective states down to primitive geometric constraints, establishing a theoretical path for biophysical reversibility. Finally, temporal anomalies in quantum measurement are addressed as processing artifacts of scale-dependent latency, introducing an alternative analytical pathway via post-facto state verification of stabilized structural footprints in the local medium. This conceptual framework offers an open integrative vocabulary bridging structural manifestation across quantum biology, computational biophysics, and complex systems theory.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-27
DOI
https://doi.org/10.5281/zenodo.22132868
Primary Topic
Fractal and DNA sequence analysis
Type
preprint
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preprint

The Universal Information Lattice: An Informational Topology Framework for Scale-Invariant Morphogenesis, Multifractal Criticality, and Non-Linear Temporal Trajectories

Lom Lucia
Zenodo (CERN European Organization for Nuclear Research)
Fractal and DNA sequence analysis
preprint

The Universal Information Lattice: An Informational Topology Framework for Scale-Invariant Morphogenesis, Multifractal Criticality, and Non-Linear Temporal Trajectories

Lom Lucia
preprint en

Abstract

This preprint introduces the Universal Information Lattice (UIL), a synthetic informational topology framework postulating that four-dimensional spacetime and physical mass distribution are emergent phenomena generated by a sub-quantum thermodynamic matrix. By integrating principles of self-organized criticality (SOC), molecular bioelectricity, and the free-energy principle, the framework establishes a multi-tiered reduction cascade where scale-invariant topological constraints restrict macro-cellular state spaces. Rather than relying on traditional genetic determinism, this model offers a non-chemical, purely geometric mechanism for tissue boundary regulation through gap-junction discontinuities and localized topological frustration. Furthermore, oncological decoupling (cancer) is re-classified as a macrostructural execution error resulting from a localized symmetry collapse from collective states down to primitive geometric constraints, establishing a theoretical path for biophysical reversibility. Finally, temporal anomalies in quantum measurement are addressed as processing artifacts of scale-dependent latency, introducing an alternative analytical pathway via post-facto state verification of stabilized structural footprints in the local medium. This conceptual framework offers an open integrative vocabulary bridging structural manifestation across quantum biology, computational biophysics, and complex systems theory.

Zenodo (CERN European Organization for Nuclear Research)
Fractal and DNA sequence analysis
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The Universal Information Lattice: An Informational Topology Framework for Scale-Invariant Morphogenesis, Multifractal Criticality, and Non-Linear Temporal Trajectories — Lom Lucia · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS