Quantum-Inspired Optimization via Wave Function Collapse

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum-inspired optimization aims to leverage quantum mechanical phenomena to accelerate and improve the performance of optimization algorithms. This paper introduces a novel approach utilizing wave function collapse to guide the search process, demonstrating its potential for enhanced efficiency and solution quality. We formulate the optimization problem as a quantum system, employing wave function collapse to create a probabilistic exploration of the solution space. The paper details the algorithm's design, the mechanics behind wave function collapse, and its performance evaluation against established optimization techniques. The core claim is that this approach offers a significant advancement in optimization, particularly for complex problems where traditional methods struggle.

DOI: 10.5281/zenodo.22183652

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