Title: Adaptive Quantum Topologies for Quantum Computation

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel quantum computation model based on adaptive quantum topology control. The core idea is to leverage the inherent self-similarity of quantum topology to enhance the adaptability and robustness of quantum computations. The model employs a dynamically adjusted parameter set to optimize quantum processor performance, offering significant advantages over current approaches. This approach addresses key limitations in quantum computation, specifically the dependence on precise qubit control. We present a detailed theoretical framework and preliminary experimental results demonstrating the effectiveness of this model, showcasing potential improvements in quantum algorithm performance and error mitigation. The research highlights the transformative potential of harnessing quantum topology for enhanced quantum computing capabilities.

DOI: 10.5281/zenodo.22203482

Related papers

Title: Adaptive Topology-Based Quantum Computing Parameter Adjustment

Jincheng Zhang

Quantum computing offers the potential for unprecedented computational power, but its practical application is hampered by the need for precise control over quantum systems. This paper investigates a novel parameter adjustment framework based on adaptive topology, aiming to enhance quantum computing efficiency through dynamic manipulation of quantum state. We propose a method that dynamically adjusts quantum qubit parameters based on the observed outcome of quantum computations, leveraging the principles of adaptive algorithms to optimize resource utilization. The core mechanism revolves around a self-learning algorithm that continuously refines parameter values to maximize fidelity and minimize error rates, thereby improving the performance of quantum algorithms. This work introduces a new approach to parameter tuning, moving beyond static approaches and embracing a dynamic, adaptive strategy. The paper explores the potential advantages of this framework and presents preliminary results demonstrating its effectiveness in a simulated environment.

Sep 3, 20260 citations

Title: Topological拓扑拓扑 Framework for Quantum Computing

Jincheng Zhang

Quantum computing is a rapidly advancing field with immense potential to revolutionize various industries. However, current quantum computing architectures face significant challenges, primarily related to the need for complex control and optimization. This paper introduces a novel quantum computing framework based on topological topology, specifically leveraging self-similarity to enhance computational efficiency and control. The framework provides a robust and adaptable approach to quantum algorithm design and optimization, offering a significant advancement over existing methods. We detail the core mechanism of utilizing self-similarity to achieve improved performance and demonstrate its effectiveness through theoretical analysis and preliminary experimental validation. The goal is to build a quantum computing paradigm that is both highly efficient and resilient to noise.

Sep 3, 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

Title: Topological Quantum Computing Self-Adaptation

Jincheng Zhang

The development of robust and efficient quantum computing is paramount for realizing transformative technologies. Traditional quantum algorithms often rely on pre-defined parameters, limiting their adaptability and hindering performance in complex scenarios. This paper explores the potential of topological quantum computing and self-adaptive algorithms to overcome these limitations. We investigate a novel approach utilizing dynamically adjusted topological structures to optimize quantum computations, addressing the core claim that research is underway to design self-adaptive quantum computing systems capable of adjusting their topology in response to input data, thereby enhancing both efficiency and stability. This approach leverages adaptive algorithms to dynamically reshape the quantum system's topology, offering a pathway towards more versatile and reliable quantum computation. The research demonstrates the potential for significant advancements in quantum algorithms and system design through this self-adaptive methodology.

Aug 29, 20260 citations

Title: Adaptive Topological Transformation Quantum Computing Model (QATQ)

Jincheng Zhang

This paper introduces a novel quantum computing model, QATQ, based on adaptive topological transformation techniques. We propose a framework that dynamically adjusts the quantum state evolution to simulate system dynamics and leverages topological structures for optimization. The core mechanism focuses on combining quantum algorithms with adaptive topological transformations to improve efficiency and address the challenges of traditional quantum algorithms. This research explores the potential of QATQ to enhance the performance of various quantum computations, offering a fundamentally different approach to quantum system modeling. The paper details the methodology, provides a theoretical analysis, and presents preliminary experimental results demonstrating the efficacy of the QATQ approach. The study aims to advance the state of quantum computing by introducing a dynamic and adaptive method.

Sep 7, 20260 citations

Title: Adaptive Quantum Computing Parameter Adjustment via Quantum Topology

Jincheng Zhang

Quantum computing offers unprecedented computational power, but achieving optimal performance requires careful parameter tuning. Conventional optimization algorithms often require manual adjustments, limiting scalability and efficiency. This paper proposes a novel algorithm, based on quantum topology, for adaptive parameter adjustment in quantum computing. We introduce a mechanism that leverages the inherent topological properties of quantum systems to automatically adjust parameters, leading to optimized computational results. The algorithm's core is the utilization of quantum topology to dynamically modify the quantum state, facilitating a pathway towards more efficient and robust quantum computation. We detail the algorithm's design, its theoretical foundations, and preliminary experimental results demonstrating its potential for improved parameter optimization. This work presents a paradigm shift toward automated parameter tuning, promising significant advancements in quantum algorithm design and performance.

Sep 3, 20260 citations