Adaptive Microscopic Quantum Computing Optimization

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper explores the potential of incorporating adaptive geometric optimization into the design and operation of micro-quantum computers. The core claim is that a novel framework leverages quantum entanglement and dynamically adjusted geometric transformations to optimize the state of quantum systems, ultimately leading to enhanced computational efficiency and precision. We investigate the fundamental principles behind this approach, detailing the design of the optimization algorithm and its application to a specific quantum system. The study explores how the interplay of quantum entanglement and geometric manipulation can provide a pathway to significantly improve the performance of quantum computations.

DOI: 10.5281/zenodo.22252584

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