Dynamic Topological Adaptive Quantum Computing

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper proposes a novel approach to quantum computing termed "Dynamic Topological Adaptive Quantum Computing," addressing the limitations of static quantum architectures. The core concept revolves around the ability of a quantum topology to dynamically reshape itself based on input data, maximizing efficiency in quantum algorithm execution. This is achieved by leveraging entangled states within a quantum topological network, coupled with machine learning algorithms. These algorithms enable real-time adjustments to quantum bit connectivity and gate operations, optimizing both circuit pathways and overall efficiency. Unlike existing quantum computing paradigms reliant on fixed topologies, this adaptive system represents a significant advancement, offering the potential for dramatically improved performance and scalability. The theoretical framework presented outlines the key components and operational principles, highlighting the potential for a fundamentally new approach to quantum computation. We explore the mathematical underpinnings of this system, focusing on the control and manipulation of entangled states and the optimization of quantum circuits.

DOI: 10.5281/zenodo.22199187

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