Dimension Generalization Algorithm with Quantum Entanglement Coupling Principle

Jincheng Zhang

Published Aug 29, 2026• 0 citations

Abstract

This paper introduces a novel dimension generalization algorithm leveraging quantum entanglement to facilitate complex operations within high-dimensional spaces. Traditional approaches often rely on specific quantum entanglement patterns, presenting limitations in scalability and operational complexity. Our proposed method proposes a system utilizing a "quantum-induced state" that allows for a more generalized approach to dimension expansion, bypassing the need for direct entanglement manipulation. This offers a potential pathway to reduce entanglement costs and enhance the algorithm's overall feasibility. We demonstrate the effectiveness of this approach through a series of carefully designed simulations, highlighting its potential to improve the computational efficiency and broaden the applicability of dimension generalization techniques. The core mechanism centers around a dynamically generated quantum state that effectively "quantizes" the dimension space, enabling novel manipulations without the inherent challenges associated with entanglement.

DOI: 10.5281/zenodo.22152749

Related papers

Dimension Expansion Algorithm

Jincheng Zhang

This paper introduces a novel Dimension Expansion Algorithm (DEA) leveraging quantum entanglement to dynamically extend the dimensional landscape for simulation purposes, particularly with emphasis on potential applications in quantum computing and exploration of hypothetical multi-dimensional spaces. The algorithm constructs a 'quantum entanglement dimension' that allows for the manipulation and expansion of a system's state space, mirroring the principles of quantum mechanics and offering a pathway to simulate complex quantum phenomena. The core mechanism centers around utilizing entanglement to establish a 'correlated dimension' – a fundamental quantum property – to facilitate the exploration of higher-dimensional spaces. We detail the algorithm's architecture, discuss its theoretical underpinnings, and present preliminary results demonstrating its capability to generate novel data spaces and explore potential quantum-related outcomes. The research explores the potential of this technique to generate complex quantum states and provide a pathway to advanced simulation methodologies.

Sep 4, 20260 citations

Dimension Mapping and Quantum Entanglement Coupling Mechanisms

Jincheng Zhang

This paper explores the potential of leveraging quantum entanglement to revolutionize quantum computing through a novel dimensionality mapping technique. We introduce a dynamic quantum entanglement network designed to create a "dimension mapping" mechanism, effectively expanding the computational space beyond the limitations of traditional quantum computers. This approach offers a potential pathway toward achieving unprecedented computational capabilities by exploiting the inherent correlations within entangled quantum systems. The core mechanism focuses on establishing a network that dynamically adjusts the quantum state to facilitate the traversal of complex multi-dimensional spaces. This study investigates the implications of this method, analyzing its potential for enhancing quantum information processing and demonstrating its feasibility through theoretical modeling and simulations. The resulting advancements hold promise for unlocking entirely new avenues of quantum algorithm design and problem-solving.

Aug 31, 20260 citations

Dimension Generalization and Quantum Entanglement: A Novel Framework for Geometry and Quantum Information

Jincheng Zhang

This paper explores the convergence of dimension generalization and quantum entanglement, proposing a novel framework for creating and manipulating high-dimensional spaces utilizing quantum entanglement. Traditional dimensionality reduction methods often struggle with the inherent complexities of high-dimensional data, while the potential of quantum entanglement offers a pathway to fundamentally alter geometric relationships. This work introduces a new mechanism, termed "dimension anchoring," that leverages entangled quantum states to dynamically adjust dimensional parameters, bypassing the need for direct manipulation of the underlying geometric structure. We demonstrate the framework's potential for generating novel geometric structures and, critically, for exploiting entanglement to enhance quantum information security. This research aims to provide a new perspective on dimensionality reduction, quantum computation, and secure communication by integrating these two powerful fields.

Sep 3, 20260 citations

Dimension Generalization and the Interaction of Quantum Entanglement

Jincheng Zhang

This paper explores the potential of leveraging quantum entanglement to facilitate the precise simulation of quantum phenomena within high-dimensional spaces. We propose a novel dimensionality extension technique, termed "Quantum Entanglement Self-Adaptation," that utilizes the inherent properties of quantum entanglement to dynamically adjust the dimensionality of the simulation, thereby mitigating the inherent errors associated with traditional dimensionality reduction techniques. The core mechanism of this approach centers around establishing a self-adaptive entanglement structure that adjusts the simulation space's geometry in response to the quantum state, offering a pathway towards more accurate and robust simulations. The resulting framework addresses the limitations of current methods by providing a fundamentally different approach to dimensionality extension, potentially unlocking new capabilities in quantum simulation.

Sep 4, 20260 citations

Dimension Generalization with Quantum Entanglement

Jincheng Zhang

This paper investigates the integration of dimensionality generalization and quantum entanglement to achieve highly accurate geometric modeling. The core claim is to develop a novel method leveraging quantum entanglement to map low-dimensional spaces to higher-dimensional spaces, utilizing entanglement for precise geometric calculations and enabling high-precision modeling. We propose a quantum computing algorithm designed to perform geometric computations within low-dimensional spaces, guided by the entangled states generated by this process. This approach offers a fundamentally new pathway for geometric data analysis and modeling, potentially surpassing the limitations of classical techniques. The paper explores the potential of this combination to address challenges in geometric representation and precise calculation, highlighting the key mechanisms involved and outlining future research directions.

Sep 7, 20260 citations

Dimensional Geometry Adaptive Quantum Computing

Jincheng Zhang

This paper investigates the potential of dimensionality-aware quantum computing, specifically exploring the concept of a novel approach that leverages quantum entanglement to expand computational space beyond the limitations of classical physics. We introduce a new method for manipulating quantum states through a geometric transformation, enabling calculations in higher dimensions without the need for traditional positional operations. The core mechanism centers around establishing a quantum entanglement network to directly map quantum states to higher-dimensional spaces, exploiting the correlated nature of entanglement to perform computations. The study aims to demonstrate the feasibility of this approach, highlighting its potential to address complex problems currently intractable for classical computers. The proposed method promises a paradigm shift in quantum algorithm design and offers a pathway to fundamentally expand the capabilities of quantum computation.

Aug 31, 20260 citations