Quantum-Inspired Constraint Propagation with Memory

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum-Inspired Constraint Propagation with Memory explores the potential of quantum computing to accelerate constraint satisfaction problems. This paper introduces a novel approach leveraging quantum memory to efficiently represent and retrieve constraints, allowing for faster exploration of the search space. We detail the implementation of a quantum circuit that stores and retrieves information about past states, enabling a significant reduction in the computational complexity compared to classical methods. The core mechanism focuses on harnessing quantum memory to capture and manipulate state information, leading to improved performance in constraint satisfaction scenarios. The research presents a preliminary investigation into the feasibility and potential advantages of this quantum-inspired constraint propagation technique.

DOI: 10.5281/zenodo.22483751

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