Quantum-Inspired Algorithmic Memory

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper explores a novel approach to algorithmic memory design, drawing inspiration from quantum mechanics. The core idea is to emulate quantum coherence principles—specifically superposition and entanglement—to construct a more robust and resilient memory system. Traditional algorithmic memory structures often suffer from significant data loss due to bit flips and other errors. Our proposed system, termed "Quantum-Inspired Algorithmic Memory," utilizes a hierarchical architecture where information is encoded across multiple levels of abstraction, akin to the layered structure found in quantum systems. This approach aims to dramatically reduce data loss by exploiting the inherent redundancy and error-correction capabilities associated with quantum phenomena. We will detail the mathematical framework underpinning this architecture, focusing on the principles of superposition, entanglement, and decoherence mitigation. The system's performance will be evaluated through theoretical analysis and the derivation of key equations governing its operation. Ultimately, this research suggests a pathway toward creating memory systems capable of maintaining data integrity in challenging environments.

DOI: 10.5281/zenodo.22247957

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