拓扑量子几何的自适应自组装

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel approach to topology quantum geometry, termed "Adaptive Topological Geometry" (ATG), which leverages quantum entanglement to dynamically modify topological structures and enable highly efficient computation and information storage. The core mechanism centers around a "Quantum Topology Key" (QTK) system, utilizing entangled pairs to guide the evolution of topology and control the dynamics of topological changes. We demonstrate the effectiveness of ATG through simulations and preliminary results, showcasing its ability to achieve unprecedented levels of computational speed and data storage density. The paper highlights the significance of this approach in pushing the boundaries of computational capabilities. This research explores a fundamentally new paradigm for topology, emphasizing the role of quantum entanglement in shaping and controlling topological structures.

DOI: 10.5281/zenodo.22204684

Related papers

拓扑量子几何的自适应拓扑结构

Jincheng Zhang

Abstract: The study of topology and quantum geometry has long been a frontier of mathematical research, offering potential solutions to longstanding problems in physics and computer science. This paper explores the application of a novel approach, termed "拓扑量子几何", which leverages the principles of quantum entanglement to dynamically adjust the topology of a geometric structure. We propose a framework where the underlying structure undergoes continuous evolution driven by quantum interactions, enabling unprecedented computational speeds and data compression capabilities. This work introduces a self-adaptive topology, addressing the limitations of traditional methods in complex scenarios, and provides a theoretical foundation for its practical implementation. The core mechanism centers around the precise orchestration of entangled states to induce structural transformations. The resulting system exhibits enhanced computational efficiency and the potential for drastically reduced data storage requirements. The exploration of this framework offers a significant advancement in the field, representing a paradigm shift in how topology can be manipulated for computational tasks.

Sep 4, 20260 citations

Dynamic Topology Geometry and Adaptive Topological Structures

Jincheng Zhang

This paper explores the intersection of dynamic topology geometry and quantum entanglement, proposing a novel approach to quantum information processing and storage through the design of a self-adaptive topological structure. We introduce a dynamic topology model predicated on quantum entanglement, utilizing instantaneous state changes to control the evolution of the topology, and integrating this with the principles of quantum computation. The core mechanism centers on creating entangled states that act as a dynamic "blueprint" guiding the topology's transformation. The resulting geometry offers enhanced computational efficiency and potential for novel quantum phenomena. This work investigates the feasibility of leveraging entangled states to dynamically shape topological structures, ultimately providing a pathway to more efficient and versatile quantum information handling.

Sep 3, 20260 citations

Quantum Topologies: Adaptive Geometry Modeling

Jincheng Zhang

Quantum Topologies represent a fascinating intersection of quantum mechanics and topology, offering a unique paradigm for computation and information processing. This paper explores the development of an adaptive geometry modeling framework, leveraging quantum entanglement and topological structure to dynamically map and control quantum states, and ultimately, pushing the boundaries of quantum computation. We propose a novel approach that utilizes quantum entanglement as a key mechanism for achieving this dynamic control, offering a potential pathway to overcome the limitations of traditional quantum computing. The framework's core claim is that establishing such a modeling system will lead to significant breakthroughs in quantum algorithms and computational capabilities.

Aug 29, 20260 citations

Quantum Topological Entanglement Field

Jincheng Zhang

Quantum topological entanglement fields (QTEFs) represent a novel approach to quantum information processing, leveraging the principles of quantum topology to create dynamically shaped spacetime structures. This research explores the potential of QTEFs for enhancing quantum computation and communication through the implementation of self-adaptive geometric configurations. The core mechanism focuses on utilizing precise control of entangled states to achieve both information storage and transmission with unprecedented accuracy. This work addresses a gap in current research by proposing a fundamentally new paradigm for manipulating quantum information, offering the promise of exceeding the limitations of existing quantum technologies.

Sep 4, 20260 citations

基于量子拓扑的自适应几何计算

Jincheng Zhang

This paper introduces a novel quantum topological geometry computing framework, leveraging geometric topology to optimize computational processes and enhance accuracy and efficiency. The core mechanism centers around a dynamically adaptable geometry that allows for precise manipulation of parameters within a defined topological space, enabling the exploration of complex and highly sensitive systems. We demonstrate the framework's efficacy through a series of theoretical and applied examples, showcasing its ability to address challenges in various fields, including materials science, quantum control, and topology optimization. The work establishes a new paradigm for geometric computation, offering a fundamentally different approach to addressing computational problems rooted in topological principles.

Sep 4, 20260 citations

Dynamic Adaptive Topological Geometry for Quantum Entanglement Control

Jincheng Zhang

This paper explores the application of dynamic adaptive topological geometry to quantum entanglement control. The core concept revolves around leveraging quantum entanglement to dynamically modify the topology of a geometric structure, enabling precise geometric transformations and facilitating quantum computations. We present a novel algorithm that utilizes entangled states to control the evolution of topological parameters, offering a pathway towards enhanced precision and control in quantum processing. The research focuses on the design of a flexible and adaptable system capable of handling the inherent complexity of quantum entanglement. The paper details the methodology, demonstrating the algorithm's efficacy through simulations and a preliminary analysis of quantum entanglement manipulation. The results suggest a significant improvement in geometric precision and control compared to traditional methods.

Sep 4, 20260 citations