Title: Non-Local Constraint Optimization for Quantum Circuits (NLOCQ)

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum circuit design presents a significant challenge due to the inherent complexity of optimizing numerous parameters across multiple qubits. Traditional optimization methods often struggle with the computational demands of fully solving the optimization problem, particularly when dealing with large quantum systems. This paper introduces Non-Local Constraint Optimization for Quantum Circuits (NLOCQ), a novel approach that leverages quantum entanglement to enable efficient and scalable optimization of quantum circuit parameters without explicitly solving the full optimization problem. NLOCQ utilizes a distributed search strategy, exploiting quantum entanglement to create a 'distributed' optimization process, thereby reducing computational burden and enabling exploration of a significantly larger search space. We demonstrate the effectiveness of NLOCQ through a series of simulations, showcasing its ability to efficiently optimize quantum circuits and achieve optimal performance compared to classical methods under specific benchmark scenarios. The core mechanism centers around creating entangled states to represent potential solutions, facilitating rapid exploration and identification of optimal parameter configurations. This work represents a significant advancement in quantum circuit optimization, offering a promising pathway to more efficient and practical quantum design.

DOI: 10.5281/zenodo.22199281

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