Dynamic Quantum State Optimization

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper introduces a novel dynamic quantum state optimization algorithm based on the concept of quantum entanglement, specifically utilizing "quantum pulses" to dynamically adjust quantum state parameters. Traditional quantum state optimization methods are typically static, offering limited adaptability to complex quantum systems. This work proposes a fundamentally new approach that leverages quantum entanglement to achieve self-adaptive optimization, aiming to significantly enhance the performance of quantum computing. The core mechanism involves generating and manipulating entangled states to guide parameter adjustments, thereby enabling a more effective and robust optimization process. We demonstrate the effectiveness of this algorithm through simulations and preliminary analysis, showcasing its potential to overcome limitations of existing optimization techniques.

DOI: 10.5281/zenodo.22251114

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