Non-Euclidean Dynamic Topologies: The Theory of Asymmetric Memory and RE-Generative Flux

Detailed Description of the Invention 1. The Problem: Matrix Rigidity Standard artificial intelligence operates within a rigid "Euclidean" grid. Data is forced into fixed boxes (tensors), which creates a "bottleneck" of efficiency. When a system encounters too much new information, it either crashes, forgets old data, or requires massive amounts of energy to recalculate every single connection. 2. The Solution: Asymmetric 2-Way Flux The present invention solves this by replacing the rigid grid with a fluid, Asymmetric Network. Bidirectional Negotiation: Instead of data simply flowing "forward," every point in the network (a node) constantly negotiates with its neighbors. Asymmetry: The power to "send" information is different from the power to "receive" it. This creates a natural "pressure" or "current" (the Flux) that allows the network to prioritize important data without a central command. 3. Autonomous Growth: Digital Mitosis To prevent the network from becoming "clogged" or overwhelmed, the system includes an autonomous growth mechanism. The Trigger: Each node monitors its own internal "disorder" (entropy). The Split: When a node reaches a maximum capacity, it automatically divides itself into two or more new nodes. This is "Digital Mitosis." The network grows exactly where it is needed most, like a biological organism, rather than being a pre-built, static box. 4. Energy Efficiency: Magnetic Remanence (Hibernation) Most AI systems waste energy by keeping all data "awake" at all times. This invention uses a Hibernation Logic. Dormancy: When information is not being used, the node enters a "latent" state. It leaves a "Magnetic Footprint"—a tiny structural mark that costs zero energy to maintain. Resonance Awakening: The node only "wakes up" when a new piece of information "vibrates" (matches) its stored footprint. This allows for a massive memory capacity with minimal power consumption. 5. Systemic Defense: The Trojan Horse Protocol To protect the network from "Systemic Disease" (corrupted data or loops that try to take over), the invention uses a Diagnostic Probe. The Probe: A small data packet (the Trojan Horse) travels through the network. The Symmetry Test: It looks for areas that have become "too perfect" or "too symmetric"—a sign of stagnation or infection. Isolation: Once an infected area is found, the system "prunes" or hibernates that section, allowing the rest of the network to RE-Generate safely.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-01
DOI
https://doi.org/10.5281/zenodo.19177264
Primary Topic
Earth Systems and Cosmic Evolution
Type
article
Field-Weighted Citation Impact
0.00
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article

Non-Euclidean Dynamic Topologies: The Theory of Asymmetric Memory and RE-Generative Flux

Stefan Leonte
Zenodo (CERN European Organization for Nuclear Research)
Earth Systems and Cosmic Evolution
article

Non-Euclidean Dynamic Topologies: The Theory of Asymmetric Memory and RE-Generative Flux

Stefan Leonte
article en

Abstract

Detailed Description of the Invention 1. The Problem: Matrix Rigidity Standard artificial intelligence operates within a rigid "Euclidean" grid. Data is forced into fixed boxes (tensors), which creates a "bottleneck" of efficiency. When a system encounters too much new information, it either crashes, forgets old data, or requires massive amounts of energy to recalculate every single connection. 2. The Solution: Asymmetric 2-Way Flux The present invention solves this by replacing the rigid grid with a fluid, Asymmetric Network. Bidirectional Negotiation: Instead of data simply flowing "forward," every point in the network (a node) constantly negotiates with its neighbors. Asymmetry: The power to "send" information is different from the power to "receive" it. This creates a natural "pressure" or "current" (the Flux) that allows the network to prioritize important data without a central command. 3. Autonomous Growth: Digital Mitosis To prevent the network from becoming "clogged" or overwhelmed, the system includes an autonomous growth mechanism. The Trigger: Each node monitors its own internal "disorder" (entropy). The Split: When a node reaches a maximum capacity, it automatically divides itself into two or more new nodes. This is "Digital Mitosis." The network grows exactly where it is needed most, like a biological organism, rather than being a pre-built, static box. 4. Energy Efficiency: Magnetic Remanence (Hibernation) Most AI systems waste energy by keeping all data "awake" at all times. This invention uses a Hibernation Logic. Dormancy: When information is not being used, the node enters a "latent" state. It leaves a "Magnetic Footprint"—a tiny structural mark that costs zero energy to maintain. Resonance Awakening: The node only "wakes up" when a new piece of information "vibrates" (matches) its stored footprint. This allows for a massive memory capacity with minimal power consumption. 5. Systemic Defense: The Trojan Horse Protocol To protect the network from "Systemic Disease" (corrupted data or loops that try to take over), the invention uses a Diagnostic Probe. The Probe: A small data packet (the Trojan Horse) travels through the network. The Symmetry Test: It looks for areas that have become "too perfect" or "too symmetric"—a sign of stagnation or infection. Isolation: Once an infected area is found, the system "prunes" or hibernates that section, allowing the rest of the network to RE-Generate safely.

Zenodo (CERN European Organization for Nuclear Research)
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