基于量子拓扑的自适应量子计算架构

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper presents a novel quantum computing architecture based on quantum topology, designed for adaptive computation. Traditional quantum computing architectures rely on fixed parameters, limiting computational possibilities. This architecture leverages quantum topology, dynamically adjusting the quantum system's structure to optimize performance. We demonstrate a practical implementation utilizing a two-qubit system to illustrate the benefits of this approach. The core mechanism involves a self-regulating topology that adapts to the problem being addressed, leading to enhanced computational efficiency. This research explores the potential of quantum topology to revolutionize computational paradigms.

DOI: 10.5281/zenodo.22242207

Related papers

基于动态量子拓扑的量子计算架构

Jincheng Zhang

This paper introduces a novel quantum computing architecture based on dynamic quantum topology. Traditional quantum computing architectures are often static, limiting the complexity and efficiency of computations. This research proposes a dynamic architecture that adapts quantum state and path adjustments based on the system's evolution, enabling more complex and efficient quantum calculations. The core mechanism involves exploiting the dynamic properties of quantum topology to optimize quantum operations and computational processes. We explore the design of this architecture, detailing its key components and potential benefits. The research presents a framework for dynamically adjusting quantum parameters, ultimately enhancing the performance of quantum algorithms.

Sep 3, 20260 citations

自适应拓扑的量子计算的参数调整算法

Jincheng Zhang

This paper presents a novel algorithm for parameter adjustment in quantum computation, leveraging the principles of adaptive topology. Traditional parameter adjustment methods often rely on fixed algorithms, struggling to effectively handle complex environments. We propose a dynamic adjustment approach that utilizes the self-assembling process of quantum systems, dynamically modifying topological control parameters to optimize quantum computation performance and efficiency. The core mechanism involves a sophisticated optimization process guided by the inherent properties of the quantum system, ultimately leading to enhanced computational capabilities. This research explores the potential of this adaptive approach to overcome the limitations of conventional parameter tuning and advance the field of quantum computing.

Sep 7, 20260 citations

Title: Adaptive Quantum Computing with Dynamic Topology

Jincheng Zhang

This paper introduces a novel quantum computing algorithm based on dynamic topology, designed for adaptive parameter adjustment. Traditional approaches rely on fixed quantum gate parameters, limiting computational capabilities. Our algorithm leverages the inherent structure of dynamic topology to automatically optimize quantum system parameters, leading to improved precision in quantum computations. This approach addresses the limitations of current quantum algorithms by providing a mechanism for self-tuning and response to system behavior. The core mechanism involves a dynamically evolving topology that adjusts quantum gates based on the system's response, ultimately enhancing the accuracy of results. The paper details the algorithm's design, demonstrates its effectiveness through illustrative examples, and discusses the potential implications for future quantum computing advancements.

Sep 4, 20260 citations

Self-Adaptive Topology for Quantum Computing Control

Jincheng Zhang

Quantum computing offers the potential for unprecedented computational power, but current approaches to control and manipulation of qubits face significant challenges. Traditional control methods often rely on fixed parameters, limiting the system's adaptability and hindering the realization of complex quantum algorithms. This paper explores the application of self-adaptive topology, a novel approach to quantum control, to enhance the efficiency and robustness of quantum computations. We present a design for an adaptive control algorithm predicated on the principles of dynamic topology, demonstrating its efficacy in optimizing quantum entanglement and improving overall system performance. The core mechanism leverages the inherent properties of topology to dynamically adjust control parameters, leading to a significant advancement in quantum system control. This work contributes to the development of more efficient and versatile quantum computing architectures.

Aug 31, 20260 citations

自适应量子拓扑的并行计算框架

Jincheng Zhang

Quantum computing holds immense potential, but realizing this potential requires sophisticated algorithms and efficient computational architectures. This paper introduces a novel parallel computing framework based on self-adaptive quantum topology, designed to automatically adjust computational parameters to optimize performance. We propose a mechanism that leverages the inherent properties of quantum topology to dynamically adapt parallel execution strategies, leading to enhanced efficiency compared to traditional approaches. The framework's core concept is the ability to dynamically optimize the parallelism by intelligently adjusting the quantum circuit's parameters based on the system's state. This addresses the limitations of static parallelization methods, offering a potentially transformative approach to quantum computation. We present a theoretical model and preliminary implementation demonstrating the framework's capabilities. The paper concludes with a discussion of future research directions and potential applications of this innovative approach.

Aug 31, 20260 citations

自适应量子拓扑拓扑结构的自适应计算

Jincheng Zhang

Quantum topology, a rapidly evolving field of physics, promises to revolutionize computational paradigms. This paper explores the potential of utilizing quantum topology to create adaptive computational frameworks, capable of dynamically adjusting complex system topology. We introduce a novel computational framework predicated on the inherent dynamic properties of quantum topology, allowing for the automated evolution of topological structures. Our core claim centers around the design of a self-adaptive computation system leveraging this dynamic structure. The mechanism involves a framework that adjusts quantum topology parameters through a feedback loop, enabling the system to respond to changing conditions and effectively explore complex topological landscapes. We detail the framework's architecture, the underlying mathematical principles, and preliminary experimental validation demonstrating its adaptability. The potential applications of this technology span diverse fields, including materials science, drug discovery, and optimization problems, highlighting the transformative impact of adaptive quantum computation. This work presents a foundational exploration of this promising avenue, demonstrating the feasibility of dynamically reshaping complex topological configurations.

Aug 31, 20260 citations