Title: Adaptive Self-Adaptive Field Theory for Quantum Computation

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper presents a novel quantum computing model based on adaptive self-adaptive field theory. The core idea is to dynamically adjust the quantum field distribution based on input data, thereby enhancing computational efficiency. We introduce a "Field Adjustment Regulator" that adapts the quantum field profile in real-time, optimizing the system for specific tasks. The model's key innovation lies in this dynamic field adjustment mechanism. This offers a significant departure from static quantum computing approaches and promises to unlock new possibilities for quantum algorithm design and implementation. The proposed framework addresses a critical challenge in quantum computing – the need for adaptive and efficient quantum operations. This research explores the potential of this approach through a detailed theoretical analysis and preliminary implementation demonstrating its effectiveness in a simplified scenario. The paper concludes with a discussion of future work and potential applications.

DOI: 10.5281/zenodo.22263638

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