Self-Adaptive Geometry Transformations for Quantum Computing

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum computing offers the potential for unprecedented computational power, but its inherent fragility necessitates careful design and implementation. This paper investigates the application of self-adaptive geometry transformations to enhance the stability and efficiency of quantum computations. We explore a novel approach to dynamically adjust geometric parameters within quantum circuits, mitigating errors caused by subtle variations in the system's environment. Through rigorous simulations and analysis, we demonstrate significant improvements in coherence times and reduced error rates compared to traditional static geometric transformations. This work represents a fundamental step towards more robust and reliable quantum algorithms.

DOI: 10.5281/zenodo.22637032

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