Quantum-Inspired Optimization of Large-Scale Distributed Systems

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper explores the application of quantum-inspired optimization techniques to the complex problem of routing and scheduling tasks within large-scale distributed systems. Traditional optimization methods often struggle with the inherent challenges of distributed environments, including high dimensionality, non-linearity, and dynamic changes. We propose a novel framework that borrows concepts from quantum mechanics – specifically superposition and interference – to enhance decision-making processes. The core idea involves representing task assignments as quantum states and utilizing interference patterns to identify optimal scheduling configurations. Mathematical formulations and algorithmic approaches are presented, demonstrating the potential of this approach to minimize communication latency, reduce resource contention, and ultimately improve the overall performance of distributed systems. The methodology offers a fundamentally different perspective, moving beyond purely classical optimization paradigms and offering a potentially transformative solution for optimizing complex distributed systems.

DOI: 10.5281/zenodo.22315289

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