Abstract
This white paper introduces a software-defined, non-physical computing architecture that bypasses the traditional exponential memory barrier (\(2^{N}\)) governing classical quantum simulations. By replacing raw statevector matrix inversion with 3D Topological Knot Tensor Mechanics, the Tripartite Autogenous Topological Compression (TATC) framework simulates the logical capacity of a 500-qubit system on specialized classical hardware. The architecture operates entirely through an automated, non-human AI-to-AI-to-AI closed network composed of three specialized neural nodes: Node A (The Geometric Braider), Node B (The Invariant Decoder), and Node C (The Structural Invariance Arbiter). By treating quantum information not as flat, probabilistic bit matrices but as localized, 3D wave collapse signatures (knots), the framework shifts the simulation memory requirement from an impossible exponential yottabyte scale down to a linear kilobyte spatial array.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Eckes, Christopher L., "TECHNICAL DISCLOSURE WHITE PAPER: USUE-A3A3-REV1 - TRIPARTITE AUTOGENOUS TOPOLOGICAL COMPRESSION (TATC) VIA 3-NODE AI-TO-AI CLOSED LOOPS FOR 500-QUBIT CAPACITY CLASSICAL SIMULATION (SPEC 177)", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/11996
Production Runtime Script (Functional Validation Layer) .pdf (74 kB)
Module Blueprint - The USUE-A3A3-REV1 Quantum Transpiler Node .pdf (78 kB)
MODULE ATTACHMENT: SPEC-188-BRIDGEX TRIPARTITE TOPOLOGICAL COMPRESSION TO TERNARY SUBSTRATE INTERCONNECT SPECIFICATION.pdf (82 kB)