Quantum Information Fusion: Adaptive Geometry for Enhanced Information Storage and Transmission

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

Quantum information fusion is a rapidly developing field with significant potential for enhancing the processing and storage capabilities of quantum systems. This paper introduces a novel quantum information fusion algorithm predicated on adaptive geometry, aiming to overcome the limitations of existing approaches. The core mechanism involves dynamically adjusting geometric structures to optimize the flow and entanglement of quantum information. We propose a method that leverages the inherent properties of geometric topology to create a flexible and efficient fusion framework. This work presents a theoretical foundation and preliminary experimental validation demonstrating the algorithm's effectiveness in integrating quantum information across various geometric contexts. The focus is on maximizing the density of entangled states and facilitating the transfer of quantum information over extended distances.

DOI: 10.5281/zenodo.22319228

Related papers

Title: Adaptive Geometry of Quantum Entanglement

Jincheng Zhang

Quantum entanglement, a cornerstone of quantum mechanics, possesses a remarkable property: its ability to correlate states across vast distances without physical transmission. However, harnessing this entanglement for practical applications, particularly in quantum information processing, faces significant challenges. This paper explores a novel approach to quantum entanglement – Adaptive Geometry of Quantum Entanglement – that leverages the inherent dynamism of quantum systems to achieve more complex and efficient information storage and manipulation. We propose a framework based on dynamically adjusting the topology of quantum systems, driven by a concept of "dynamic topology fields." This approach aims to overcome limitations of traditional entanglement-based techniques by offering a fundamentally different pathway to information processing. The core claim is that by constructing multi-scale quantum topological structures, we can achieve more complex and enhanced information storage and processing capabilities. This investigation introduces a new quantum information storage paradigm, offering a potential solution to the inherent limitations of current quantum technologies. This work investigates the theoretical foundations and potential applications of this approach, emphasizing the significance of adaptive geometry in advancing quantum computation.

Sep 2, 20260 citations

Information Entropy Based Quantum Entanglement Geometry Adaptation

Jincheng Zhang

This paper introduces a novel information-theoretic approach to geometry optimization, leveraging the principles of quantum entanglement to dynamically adjust geometric structures. We propose a model centered around quantifying information entropy as a guiding force for shaping data storage and processing efficiency. The core mechanism involves utilizing quantum entanglement to subtly influence the geometry, resulting in enhanced computational capabilities. The research explores the potential for this technique to improve data management and accelerate complex calculations. This work presents a framework for quantifying and manipulating geometric relationships through the inherent properties of quantum entanglement, ultimately aiming to achieve more efficient data processing and computation.

Sep 4, 20260 citations

Geometric Information Theory: Adaptive Topology Transformation & Quantum Algorithm Fusion

Jincheng Zhang

This paper introduces a novel hybrid algorithm combining adaptive topology transformation with quantum algorithms to achieve high-precision geometric transformations and calculations. Traditional geometric transformation methods rely on fixed topologies, while this approach leverages the adaptive transformation capabilities of geometric information theory to enable more flexible and efficient computations. The algorithm's core mechanism involves a carefully designed transformation process, guided by geometric information, which is enhanced by the inherent computational advantages of quantum algorithms. We present a theoretical framework outlining the algorithm's architecture and discuss its potential impact on various geometric computation problems. The study aims to advance the field of geometric computation by exploring a new paradigm for achieving high-precision transformations.

Sep 4, 20260 citations

Quantum Entanglement Dynamic Topological Transform

Jincheng Zhang

Quantum entanglement, a fundamental phenomenon in quantum mechanics, presents unique challenges in information processing and storage. This research explores the dynamic topological transform of quantum entanglement, aiming to enhance quantum information's storage and transmission efficiency. The core mechanism involves an adaptive algorithm that dynamically adjusts the quantum entanglement's topology through topological transformations, thereby enabling self-reconfiguration and quantum entanglement conversion. The proposed algorithm offers a novel approach to overcome limitations inherent in traditional quantum state generation methods, leveraging the power of topology to provide enhanced computational capabilities. This work presents a theoretical framework and preliminary experimental validation demonstrating the effectiveness of this dynamic topological transform in manipulating quantum entanglement.

Sep 6, 20260 citations

Dimension Expansion and Quantum Entanglement: An Adaptive Geometric Model

Jincheng Zhang

This paper introduces a novel dimension-expanding model leveraging quantum entanglement to dynamically adjust geometric structures. We propose a framework, termed "Self-Adaptive Geometry," wherein quantum entanglement governs the evolution of space, allowing for automatic adjustments to improve computational efficiency and data storage. The core mechanism focuses on integrating the inherent dynamics of entanglement into geometric transformations, creating a system capable of self-optimization. This approach offers a fundamentally new pathway for quantum computation and information processing, differentiating it from existing theoretical frameworks centered primarily on algorithmic advancements. The proposed model's potential implications for quantum algorithms and data management are substantial, representing a significant step towards a more versatile and adaptive approach to quantum systems.

Sep 3, 20260 citations

Core Claim: A Quantum-Adaptive Topology Transform Algorithm constructs and manipulates topological structures through quantum self-adaptations, enabling quantum information encoding and transmission, and exploring the capacity of quantum states.

Jincheng Zhang

Quantum information processing offers unprecedented opportunities for secure communication and data storage due to the inherent properties of quantum mechanics. This paper investigates the application of quantum self-adaptations to topology, exploring a novel algorithm for transforming topological structures. We propose a quantum-adaptive topology transform algorithm that leverages quantum self-adaptations to effectively encode and transmit quantum information. The algorithm's core mechanism involves a dynamic reshaping of topological relationships, optimizing for information preservation and enhanced transmission efficiency. This research aims to advance the field of quantum information theory by demonstrating the practical utility of this approach in constructing and manipulating topological structures. The exploration of quantum state encoding capabilities is a key focus, seeking to unlock the full potential of quantum information. This work presents a theoretical framework and preliminary experimental validation of the proposed algorithm. The significance of this research lies in its potential to develop robust and efficient quantum communication protocols based on advanced topological transformations.

Aug 31, 20260 citations