Quantum-Inspired Lattice Optimization - Adaptive Lattice Density Adjustment

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper presents a novel optimization algorithm, Quantum-Inspired Lattice Optimization (QILO), designed to address challenges in geometric optimization, specifically focusing on the placement of lattice points. Traditional lattice optimization methods often struggle with complex geometries and high-dimensional spaces. We introduce a quantum-inspired approach that utilizes superposition and interference to guide the placement of lattice points, enabling the exploration of a wider solution space and improved convergence. We detail the algorithm's core mechanism, explain the quantum state concept, and demonstrate its effectiveness through a series of illustrative examples. The paper concludes with a discussion of the potential implications of this approach for various geometric optimization problems.

DOI: 10.5281/zenodo.22201276

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