基于量子拓扑的自适应量子电路设计

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum computation, leveraging the unique properties of quantum mechanics, holds immense promise for scientific and technological advancements. However, scaling and maintaining the fidelity of quantum circuits presents significant challenges. This paper introduces a novel approach to quantum circuit design based on the principles of quantum topology, specifically utilizing the concept of topologically protected quantum states. We propose a self-adaptive circuit design methodology that automatically adjusts circuit parameters to optimize performance and efficiency. The core mechanism revolves around leveraging the inherent robustness of topological structures in quantum systems to achieve precise control and manipulation of quantum states. This method offers a significant improvement over conventional methods by automating the optimization process and enhancing the overall reliability of quantum circuits. We explore the theoretical foundations of this approach and present preliminary experimental results demonstrating its effectiveness in achieving targeted circuit improvements. The impact of this design on quantum computation efficiency is expected to be substantial.

DOI: 10.5281/zenodo.22276616

Related papers

基于量子拓扑的自适应量子计算的量子算法优化

Jincheng Zhang

Quantum computation holds immense potential for scientific discovery and technological advancement, but the development of efficient quantum algorithms is a significant challenge. This paper explores the application of quantum topology to optimize quantum algorithms, proposing a novel approach that leverages the inherent structure of quantum systems to dynamically adjust algorithm parameters, ultimately leading to enhanced computational efficiency. We introduce a method based on identifying and exploiting topological features within quantum circuits to guide optimization. The core mechanism focuses on using quantum topology to automatically re-parameterize circuits, mitigating the need for manual tuning and promoting more robust and adaptable algorithms. We present a theoretical framework and preliminary experimental results demonstrating the effectiveness of this technique. The resulting algorithm offers a promising pathway toward more efficient quantum computation, potentially bridging the gap between theoretical promise and practical implementation.

Sep 3, 20260 citations

基于自适应拓扑的量子计算算法优化

Jincheng Zhang

Quantum computing, leveraging the unique properties of quantum systems, offers the potential for unprecedented computational power. However, the development of efficient quantum algorithms is often hindered by the inherent complexity of quantum systems and the challenges of optimization. This paper introduces a novel quantum algorithm optimization method based on adaptive topology, designed to improve the performance of existing quantum algorithms. The core mechanism utilizes the self-adaptative nature of quantum spin states to dynamically adjust quantum parameters and improve the fidelity of quantum computations. We present a theoretical framework and preliminary experimental results demonstrating the effectiveness of this approach in optimizing a specific quantum circuit. The proposed method offers a promising path towards more efficient and reliable quantum computations. The core claim of the paper is that this adaptive topology-based algorithm significantly enhances the performance of quantum algorithms compared to traditional optimization techniques.

Aug 31, 20260 citations

自适应量子电路设计算法

Jincheng Zhang

Quantum computing holds immense promise for tackling complex problems currently intractable for classical computers. However, realizing this potential requires significant advancements in quantum circuit design, particularly in terms of efficiency and scalability. This paper introduces a novel self-adaptive quantum circuit design algorithm, designed to automatically adjust quantum circuit parameters based on system performance targets. The core mechanism leverages a self-learning process, iteratively refining the circuit structure to optimize key performance indicators – including qubit count, coherence time, and fidelity – thereby enhancing the overall quantum computation efficiency. We present a preliminary implementation demonstrating the algorithm's ability to achieve significant performance improvements compared to traditional approaches, highlighting its potential to accelerate the development of practical quantum devices.

Aug 31, 20260 citations

基于拓扑的量子计算的自适应量子电路设计

Jincheng Zhang

Quantum computing offers the potential for exponentially faster computations compared to classical computers, particularly for complex problems. However, the design and implementation of quantum circuits remain a significant challenge due to the inherent complexity of quantum systems. This paper explores a novel approach to quantum circuit design leveraging topological principles to automate the process of circuit optimization and achieve higher computational efficiency. We propose a new framework for automatic circuit adjustment based on topological structure, enabling the system to adapt its design based on the characteristics of the task at hand. This system aims to overcome the limitations of traditional methods by offering a more flexible and robust approach to quantum circuit creation. The research demonstrates the effectiveness of this framework through a series of simulations and analysis, showcasing its ability to generate circuits with improved performance for specific quantum algorithms. The core mechanism is the application of topological topological symmetries to the circuit structure, allowing the system to dynamically adjust parameters to achieve optimal results. This work represents a significant advancement in quantum circuit design, potentially paving the way for more efficient and scalable quantum computations.

Sep 4, 20260 citations

基于量子拓扑的自适应量子电路设计优化

Jincheng Zhang

Quantum circuits, with their inherent complexity and sensitivity to environmental fluctuations, pose significant challenges in their design and implementation. This paper presents a novel framework for quantum circuit design leveraging the principles of quantum topology, specifically a topological circuit design. We propose a self-adaptive circuit design algorithm that automatically adjusts circuit parameters to optimize performance and stability. This approach overcomes limitations of traditional circuit design by exploiting the inherent robustness and adaptability of topological structures. The framework utilizes a set of topological constraints and transformations to dynamically modify the circuit's parameters, leading to improved efficiency and stability. The results demonstrate the effectiveness of this method in optimizing circuit performance across a range of parameters.

Sep 3, 20260 citations

Dynamic Quantum Circuit Topology Optimization

Jincheng Zhang

Dynamic Quantum Circuit Topology Optimization addresses the challenges of optimizing quantum circuits for enhanced performance and stability through adaptive circuit design. This paper introduces a novel method leveraging the inherent topological properties of quantum circuits to dynamically adjust their structure, leading to improved computational efficiency and robustness. We present a framework for automatically optimizing circuit topology, incorporating a self-adaptive mechanism that responds to the circuit's state. The core mechanism centers on utilizing topological transformations to mitigate circuit bottlenecks and enhance coherence. The study demonstrates the effectiveness of this approach in optimizing specific quantum algorithms, showcasing its potential for accelerating complex computations. The research focuses on providing a practical solution for dynamically tailoring quantum circuits, offering a significant advancement over traditional optimization techniques.

Sep 7, 20260 citations