Work

Topos-Memetic Synthesis: Mathematical Foundations

Year: 2026

Type: article

Abstract: This paper outlines the core principles of Asymmetric Memory within the Topos-Memetic Synthesis (TMS) framework. Moving beyond Matrix Rigidity and Euclidean limitations, we define a computational architecture based on 2-Way Flux and Graph Neural Network (GNN) topographies. By utilizing Magnetic Remanence ('Hibernation vs. Deletion' logic) and active defense mechanisms (Rearguard Probing and the Trojan Horse Protocol), we establish a paradigm for managing systemic data—with direct applications to systemic diseases through flow engineering.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.19372864

Author: Stefan, Leonte

Language: English

Topic: Cognitive Computing and Networks

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7147465268

FWCI:

Cites:

Cited by:

Related to: