Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Quantum Computation Based on Measurement Theory

Jincheng Zhang

Published Aug 29, 2026• 0 citations
Publisher

Abstract

This paper proposes a novel computational model based on quantum measurement theory. The core idea is to treat computation as a series of quantum measurements, offering a potentially transformative paradigm for computing. We decompose computational tasks into sequences of measurements, leveraging mathematical tools from quantum measurement theory to perform calculations. The model explores the impact of the measurement process on computational efficiency. Unlike existing models rooted in classical physics, this approach directly addresses the fundamental role of measurement in information processing, potentially unlocking new computational possibilities. The model is presented with detailed mathematical formulations, focusing on measurement operators, state vectors, and the dynamics of measurement processes. The analysis aims to provide a theoretical framework for understanding and developing quantum computation based on the principles of measurement. ---

DOI
10.5281/zenodo.22155373

Related papers

Quantum-Inspired Parallel Algorithm Design Based on Quantum Mechanics Principles

Jincheng Zhang

This paper presents a novel approach to parallel algorithm design, drawing inspiration from the principles of quantum mechanics. The core idea is to leverage quantum phenomena like superposition and interference to create a fundamentally new paradigm for parallel computation. We propose a framework that decomposes a parallel algorithm into a set of quantum states, utilizes quantum entanglement to enable parallel operations, and employs quantum measurement to consolidate the results. This approach aims to unlock the full potential of parallel computing by mimicking the inherent parallelism found in quantum systems. The design focuses on a theoretical framework, without experimental validation, and presents a conceptual blueprint for future research and development in the field of quantum-inspired parallel computing. We outline the key components and mathematical formalisms underpinning this design, highlighting its potential advantages and challenges.

•Sep 3, 2026•0 citations

Quantum Entanglement Information Entropy Theory

Jincheng Zhang

Quantum entanglement, a fundamental phenomenon in quantum mechanics, presents a unique opportunity for information processing. This paper explores the theoretical framework for quantifying and manipulating this entangled state, ultimately aiming to understand its implications for quantum computation and information theory. We propose a novel entropy calculation model rooted in entangled states, linking this process directly with established mathematical expressions of information entropy. This research delves into the potential for leveraging entanglement for enhanced quantum information storage and efficient computation, highlighting a potential paradigm shift in this field. The study considers the interplay between entanglement, information theory, and the limitations of classical computation.

•Aug 31, 2026•0 citations

Understanding the Basics of Quantum Computing and Its Impact on Modern Physics

M. Venugopala Rao, M. Krishna Kishore, A. Subba Rao

Quantum computing represents a transformative approach to computation by leveraging the fundamental principles of quantum mechanics. Unlike classical computing, which operates on bits, quantum computing uses quantum bits or qubits that exist in superposition, enabling parallel processing of information. This paper introduces the foundational concepts of quantum computing—such as superposition, entanglement, and quantum gates—and explores how these principles differ from classical models. Further, it highlights the implications of quantum computing in modern physics, especially in areas like quantum simulation, cryptography, and quantum field theory. By avoiding complex mathematical derivations, this paper aims to make quantum computing accessible to a broader academic audience, emphasizing both theoretical insights and practical impacts.

International Journal For Multidisciplinary Research•Aug 12, 2025•0 citations

Based on Quantum State Reorganization for Computation

Jincheng Zhang

This paper introduces a novel computational model predicated on quantum state reorganization. The core idea centers around leveraging the inherent transformational properties of quantum states to achieve efficient computation. We present a detailed algorithmic design capable of precisely controlling the manipulation of quantum states through reorganization, ultimately enabling the execution of specified computational tasks. This approach represents a nascent quantum computing paradigm with substantial potential. The model aims to overcome limitations inherent in traditional quantum algorithms by offering a fundamentally different method for problem-solving. We explore the mathematical underpinnings of the proposed system, focusing on state vector representations, unitary transformations, and the principles of quantum state rearrangement. This work lays the groundwork for future research into this promising area, aiming for scalability and practical applications.

•Aug 31, 2026•0 citations

Quantum Entanglement Computing Paradigm: A Distributed Algorithm Approach

Jincheng Zhang

Quantum entanglement, a fundamental phenomenon in quantum mechanics, offers a potentially transformative approach to computation. This paper investigates a novel computational paradigm, dubbed the "Quantum Entanglement Computing Paradigm," which leverages the principles of quantum superposition and entanglement to achieve parallel processing and complex calculation. We propose a framework where the computational process is decomposed into discrete quantum states, and entanglement is strategically employed to facilitate information transfer and manipulation. This design aims to address limitations of traditional computing models, particularly in the realm of large-scale data analysis and optimization problems. The core mechanism involves the precise manipulation of entangled states, enabling exponential increases in computational power. We explore the potential benefits and challenges of this paradigm, highlighting the need for rigorous mathematical analysis and simulation to fully realize its capabilities. The paper concludes with a discussion of future research directions, focusing on algorithm development and experimental validation to solidify the paradigm's practical application.

•Sep 2, 2026•0 citations

Quantum Entanglement Information Modeling Framework

Jincheng Zhang

Quantum entanglement, a fundamental phenomenon in quantum mechanics, presents a unique challenge and opportunity for information processing. This paper explores the design of a novel computational framework based on quantum entanglement, aiming to directly leverage the properties of entangled states to enhance computation efficiency and facilitate the modeling of complex quantum systems. The framework will incorporate quantum state manipulation, information encoding, and secure communication protocols, offering a fundamentally different approach to computation compared to traditional methods. The core claim is that this framework will provide a powerful tool for simulating and utilizing entangled information, potentially unlocking new algorithms and computational paradigms.

•Aug 31, 2026•0 citations
This paper proposes a novel computational model based on quantum measurement theory. The core idea is to treat computation as a series of quantum measurements, offering a potentially transformative paradigm for computing. We decompose computational tasks into sequences of measurements, leveraging mathematical tools from quantum measurement theory to perform calculations. The model explores the impact of the measurement process on computational efficiency. Unlike existing models rooted in classical physics, this approach directly addresses the fundamental role of measurement in information processing, potentially unlocking new computational possibilities. The model is presented with detailed mathematical formulations, focusing on measurement operators, state vectors, and the dynamics of measurement processes. The analysis aims to provide a theoretical framework for understanding and developing quantum computation based on the principles of measurement. ---
This paper presents a novel approach to parallel algorithm design, drawing inspiration from the principles of quantum mechanics. The core idea is to leverage quantum phenomena like superposition and interference to create a fundamentally new paradigm for parallel computation. We propose a framework that decomposes a parallel algorithm into a set of quantum states, utilizes quantum entanglement to enable parallel operations, and employs quantum measurement to consolidate the results. This approach aims to unlock the full potential of parallel computing by mimicking the inherent parallelism found in quantum systems. The design focuses on a theoretical framework, without experimental validation, and presents a conceptual blueprint for future research and development in the field of quantum-inspired parallel computing. We outline the key components and mathematical formalisms underpinning this design, highlighting its potential advantages and challenges.
Quantum entanglement, a fundamental phenomenon in quantum mechanics, presents a unique opportunity for information processing. This paper explores the theoretical framework for quantifying and manipulating this entangled state, ultimately aiming to understand its implications for quantum computation and information theory. We propose a novel entropy calculation model rooted in entangled states, linking this process directly with established mathematical expressions of information entropy. This research delves into the potential for leveraging entanglement for enhanced quantum information storage and efficient computation, highlighting a potential paradigm shift in this field. The study considers the interplay between entanglement, information theory, and the limitations of classical computation.
Quantum computing represents a transformative approach to computation by leveraging the fundamental principles of quantum mechanics. Unlike classical computing, which operates on bits, quantum computing uses quantum bits or qubits that exist in superposition, enabling parallel processing of information. This paper introduces the foundational concepts of quantum computing—such as superposition, entanglement, and quantum gates—and explores how these principles differ from classical models. Further, it highlights the implications of quantum computing in modern physics, especially in areas like quantum simulation, cryptography, and quantum field theory. By avoiding complex mathematical derivations, this paper aims to make quantum computing accessible to a broader academic audience, emphasizing both theoretical insights and practical impacts.
This paper introduces a novel computational model predicated on quantum state reorganization. The core idea centers around leveraging the inherent transformational properties of quantum states to achieve efficient computation. We present a detailed algorithmic design capable of precisely controlling the manipulation of quantum states through reorganization, ultimately enabling the execution of specified computational tasks. This approach represents a nascent quantum computing paradigm with substantial potential. The model aims to overcome limitations inherent in traditional quantum algorithms by offering a fundamentally different method for problem-solving. We explore the mathematical underpinnings of the proposed system, focusing on state vector representations, unitary transformations, and the principles of quantum state rearrangement. This work lays the groundwork for future research into this promising area, aiming for scalability and practical applications.
Quantum entanglement, a fundamental phenomenon in quantum mechanics, offers a potentially transformative approach to computation. This paper investigates a novel computational paradigm, dubbed the "Quantum Entanglement Computing Paradigm," which leverages the principles of quantum superposition and entanglement to achieve parallel processing and complex calculation. We propose a framework where the computational process is decomposed into discrete quantum states, and entanglement is strategically employed to facilitate information transfer and manipulation. This design aims to address limitations of traditional computing models, particularly in the realm of large-scale data analysis and optimization problems. The core mechanism involves the precise manipulation of entangled states, enabling exponential increases in computational power. We explore the potential benefits and challenges of this paradigm, highlighting the need for rigorous mathematical analysis and simulation to fully realize its capabilities. The paper concludes with a discussion of future research directions, focusing on algorithm development and experimental validation to solidify the paradigm's practical application.
Quantum entanglement, a fundamental phenomenon in quantum mechanics, presents a unique challenge and opportunity for information processing. This paper explores the design of a novel computational framework based on quantum entanglement, aiming to directly leverage the properties of entangled states to enhance computation efficiency and facilitate the modeling of complex quantum systems. The framework will incorporate quantum state manipulation, information encoding, and secure communication protocols, offering a fundamentally different approach to computation compared to traditional methods. The core claim is that this framework will provide a powerful tool for simulating and utilizing entangled information, potentially unlocking new algorithms and computational paradigms.