Quantum State Optimization through Non-Linear Geometry

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum state optimization is a critical challenge in the development of quantum devices, requiring precise control over quantum states to maximize performance. Traditional optimization methods often struggle with complex, non-linear geometry, limiting the potential for significant improvements. This paper proposes a self-optimizing algorithm that leverages non-linear geometry to dynamically adjust quantum state geometry, enhancing device performance. We demonstrate the effectiveness of this approach through a novel simulation and analysis of a quantum system, highlighting its ability to achieve superior results compared to existing optimization techniques. The core mechanism centers around constructing a geometric structure that responds directly to data, enabling adaptive optimization. This work presents a fundamentally new approach to quantum state optimization, potentially unlocking new levels of device capability.

DOI: 10.5281/zenodo.22268911

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