Dimension Generalization and the Correlation of Quantum Entanglement

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

This paper explores the potential synergy between dimensionality generalization and the correlation of quantum entanglement, focusing on the development of a novel computational framework that leverages entanglement to address the limitations of classical computation. We propose a new approach to quantum computing centered around the "dimension mapping" mechanism, which dynamically translates quantum states across multi-dimensional spaces to extract information. This research investigates the feasibility of utilizing entanglement as a key element in enabling the processing of ultra-high-dimensional spaces and ultimately contributes to exploring quantum computation's potential for enhanced capabilities. The core claim centers on the construction of a fundamentally new computational paradigm that extends beyond the constraints of conventional algorithms, potentially unlocking novel quantum applications.

DOI: 10.5281/zenodo.22223429

Related papers

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 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

维度泛化与量子纠缠关联

Jincheng Zhang

This paper explores the intersection of quantum entanglement and dimensional generalization, proposing a novel quantum computing model capable of achieving ultra-space quantum computation. We introduce a mechanism predicated on quantum entanglement that dynamically maps the complexity of quantum entanglement to the dimensions of a higher-dimensional space, effectively bridging the gap between the quantum realm and the potential for computational breakthroughs. The core algorithm leverages this mapping to enhance computational efficiency. The study highlights the potential of this approach to surpass existing quantum computing paradigms by offering a fundamentally new way to represent and manipulate quantum information. This work contributes to the ongoing investigation of quantum entanglement as a crucial resource for advanced computational architectures.

Sep 3, 20260 citations

Quantum Entanglement in a Non-Classical Computing Paradigm

Jincheng Zhang

Quantum entanglement, a bizarre phenomenon where two or more particles become inextricably linked, holds immense promise for revolutionizing computation. This paper explores the potential of utilizing quantum entanglement to develop a novel computing paradigm, termed "Quantum Entanglement-Driven Computation" (QEDC). We propose a model centered around a 'correlations' calculation framework, leveraging entanglement for information processing and data encoding. The core mechanism focuses on establishing a dynamic relationship between classical and quantum systems, enabling exponential computational capabilities. This approach aims to overcome the limitations of classical computing by effectively utilizing entanglement to perform calculations beyond the reach of conventional algorithms. The research highlights the potential for QEDC to address key challenges in computational complexity and information security.

Sep 4, 20260 citations

Quantum Entanglement for Asymmetric Computation

Jincheng Zhang

Quantum entanglement, a fundamental phenomenon in quantum mechanics, holds immense potential for revolutionizing computation. This paper explores the development of a novel computational paradigm based on entangled quantum states, aiming to achieve non-symmetric computation and expand into the realm of quantum computing beyond classical limitations. We present a core mechanism for harnessing entanglement's inherent asymmetry to enhance computational efficiency and unlock new capabilities. The research focuses on algorithmic design and analysis to demonstrate the feasibility of this approach. The central claim is that this framework can facilitate the execution of complex calculations leveraging the unique properties of entangled quantum states, ultimately pushing the boundaries of quantum computing.

Sep 3, 20260 citations