Quantum Information Self-Adaptive Geometry

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

Quantum information has emerged as a transformative force across various scientific and technological domains. This research explores the potential of leveraging geometric information – a concept often overlooked in current quantum computing paradigms – to enhance the capabilities of quantum computation. We propose a novel algorithm, the "Geometric Self-Adaptive Algorithm" (GSFA), that utilizes quantum entanglement to dynamically modify geometric representations of information, achieving unprecedented precision in encoding and manipulating information within quantum states. This work introduces a fundamental shift in how we approach quantum information processing, focusing on the inherent properties of entanglement and the transformative potential of geometric encoding. The core mechanism centers around the design of a specialized algorithm that actively adapts to the specific characteristics of entangled states. This adaptation is achieved through a carefully orchestrated interplay between quantum entanglement, geometric transformations, and a feedback mechanism, ultimately leading to enhanced quantum information processing capabilities.

DOI: 10.5281/zenodo.22222912

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