Adaptive Self-Inspired Quantum Computing Framework

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces an adaptive self-inspired quantum computing framework designed to enhance the efficiency and stability of quantum computations by dynamically adjusting quantum operations based on system self-inspironment. Current quantum computing paradigms often struggle with the inherent complexity of quantum systems. We propose a novel framework that incorporates self-inspired control mechanisms to dynamically optimize quantum operations, yielding improved performance and robustness. This work addresses a critical gap in quantum computing research by providing a practical solution to the challenges associated with managing quantum systems. The framework utilizes a dynamically adjusted control strategy, ensuring optimal resource utilization and minimizing errors. This paper presents a detailed theoretical analysis and preliminary experimental validation of the proposed approach.

DOI: 10.5281/zenodo.22195351

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