Quantum Computing Algorithm Optimization
Year: 2026
Type: preprint
Abstract: This paper presents a novel algorithm optimization method leveraging the unique capabilities of quantum computing. Traditional optimization algorithms often struggle with complex systems, requiring significant computational resources and time. We propose a quantum-enhanced optimization approach designed to overcome these limitations by utilizing quantum parallelism and superposition. The core mechanism involves mapping the optimization problem onto a quantum state representation, enabling parallel processing and enhanced exploration of the solution space. The paper details the design of the quantum algorithm, its potential advantages over classical approaches, and preliminary experimental results demonstrating its effectiveness in specific optimization scenarios.
Author: Zhang, Jincheng
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7210266362
Cites:
Cited by:
Related to: