Quantum Entanglement-Based Constraint Optimization

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum entanglement offers a potentially revolutionary approach to constraint optimization, a fundamental problem in various fields including logistics, finance, and materials science. This paper explores the concept of utilizing entanglement to enhance the exploration of search spaces, providing a fundamentally different algorithmic strategy compared to traditional methods. We present a novel framework predicated on correlated quantum states and propose a quantum algorithm designed to significantly accelerate optimization processes. This work aims to demonstrate the potential of entanglement to unlock new capabilities in constraint optimization, addressing limitations inherent in classical approaches.

DOI: 10.5281/zenodo.22193448

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