Multi-Dimensional Spatial Information Retrieval via Quantum Algorithms: Optimization

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper presents a novel quantum algorithm for optimizing multi-dimensional spatial information retrieval. Traditional information retrieval methods struggle with the exponential growth of complexity in high-dimensional spaces. We propose a quantum approach leveraging superposition and interference to drastically improve search efficiency. The core concept involves mapping the retrieval space into a quantum state space, utilizing quantum entanglement for parallel search across multiple dimensions, and employing quantum measurement to rapidly pinpoint the target information. The algorithm's performance is theoretically analyzed, demonstrating a potential speedup compared to classical algorithms. Specifically, we outline a framework for constructing a quantum index and detailing the steps involved in the search process. The key elements of the algorithm are the quantum state preparation, entanglement generation, and the final measurement stage. We provide a mathematical formulation of the core operations, focusing on the quantum circuit design and the probability amplitudes involved. The optimization strategy relies on minimizing the number of quantum gates required while maintaining the algorithm's effectiveness. The ultimate goal is to provide a robust and scalable quantum solution for spatial information retrieval, addressing the limitations of current classical methods.

DOI: 10.5281/zenodo.22244524

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