Quantum-Inspired Optimization via Adaptive Sampling (QIAO)

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

This paper introduces Quantum-Inspired Optimization via Adaptive Sampling (QIAO), a novel technique for complex system optimization. Traditional optimization methods often struggle with the inherent complexity of real-world problems, frequently requiring exhaustive search or computationally expensive approximations. QIAO leverages quantum-inspired principles to dynamically sample regions of the solution space, focusing on areas exhibiting higher potential for improvement. This adaptive sampling strategy significantly enhances efficiency compared to traditional methods, particularly in scenarios with high dimensionality and complex interactions within the system. We present a detailed explanation of the algorithm's design, its implementation, and preliminary results demonstrating its efficacy in a simulated optimization problem. The focus is on demonstrating the practical advantages of this approach through a quantifiable improvement in performance.

DOI: 10.5281/zenodo.22221970

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