Information Entropy Adaptive Quantum Computing

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Information entropy, a fundamental concept in information theory, provides a quantitative measure of disorder or randomness within a system. In the context of quantum computing, it serves as a critical parameter for evaluating the quality of quantum states and guiding the design of quantum algorithms. This paper explores the application of information entropy as a dynamic control mechanism within a quantum computation framework, aiming to enhance the fidelity and efficiency of quantum operations. We propose a novel quantum computing architecture that leverages information entropy to automatically adapt quantum states, minimizing noise and maximizing computational performance. The core mechanism centers around the iterative adjustment of quantum potential fields, driven by the continuous monitoring and response to changes in the system's entropy. This approach offers a promising pathway toward more robust and scalable quantum computation.

DOI: 10.5281/zenodo.22185537

Related papers

Quantum Information Entropy: Dynamic Computation and Optimization

Jincheng Zhang

Quantum information entropy, a fundamental measure of uncertainty, is a cornerstone of quantum mechanics and a critical factor in the design of quantum algorithms and systems. This paper investigates the application of dynamic computation techniques, leveraging quantum information entropy, to optimize quantum system performance and efficiency. We propose a novel algorithm that dynamically calculates and optimizes quantum systems based on the inherent properties of this entropy, aiming to maximize information utilization and improve overall system functionality. The core mechanism centers around a quantum-state evolution algorithm that adapts to the system's state, dynamically adjusting parameters to achieve optimal performance. This work introduces a new approach to quantum system optimization, demonstrating potential improvements in key metrics including fidelity and reduced error rates.

Sep 5, 20260 citations

Quantum Information Entropy Dynamics – A Dynamic Calculation Based on Quantum State Adaptation

Jincheng Zhang

Quantum information entropy is a fundamental property of quantum systems, representing the uncertainty associated with the system's state. Efficiently compressing and transmitting quantum information requires minimizing the entropy, while simultaneously maximizing the fidelity of the transmitted states. This paper proposes a novel dynamic calculation method for quantum information entropy, leveraging the inherent adaptability of quantum states to achieve enhanced compression and transmission efficiency, particularly in the context of quantum information transfer. The core mechanism centers around utilizing quantum state adaptation to dynamically adjust the system's state, thereby minimizing the entropy without compromising fidelity. This approach offers a fundamentally different pathway to data management compared to traditional methods, potentially revolutionizing quantum communication protocols.

Sep 3, 20260 citations

Dynamic Information Fields (DIF) Theory

Jincheng Zhang

This paper presents a novel Dynamic Information Field (DIF) theory, integrating information theory and quantum field theory to investigate non-linear effects of information in quantum systems and applying this framework to quantum computation optimization and control. We develop a mechanism where information serves as a critical parameter, leveraging the non-linear properties of information entropy to design quantum algorithms. The core claim is that the theory provides a new perspective on quantum computation, offering potential improvements in algorithm efficiency and robustness. The work explores the connection between information and quantum state evolution, and demonstrates the utility of information entropy in guiding the design of quantum algorithms. The theoretical framework is presented as a means to enhance the understanding of quantum systems and advance the field of quantum computation.

Aug 31, 20260 citations

Quantum Information Fields: Adaptive Mapping

Jincheng Zhang

Quantum information fields are a fundamental concept in quantum mechanics, and their study has garnered significant attention due to their potential for revolutionary advancements in computation and communication. This paper explores the concept of adaptive mapping, a novel approach to quantum information field design that leverages the unique properties of quantum entanglement to dynamically adjust the field's characteristics, thereby enhancing both quantum computing efficiency and quantum communication security. The core aim is to exploit the inherent responsiveness of quantum systems to external influences, offering a pathway towards more robust and versatile quantum technologies. We detail the design of a specific adaptive mapping framework, outlining its theoretical underpinnings and potential practical applications. This work addresses a critical gap in current research by focusing on the integration of entanglement into a dynamic field adjustment mechanism. The resulting system promises to overcome limitations in existing approaches, potentially unlocking new frontiers in quantum information processing and security.

Sep 5, 20260 citations

Topological Quantum Topology Adaptive Computing

Jincheng Zhang

This paper investigates the potential of adaptive quantum computing, a novel approach designed to enhance efficiency and robustness through dynamic algorithm adjustment. We outline a theoretical framework for a quantum computing algorithm that continuously monitors the quantum system's state, intelligently selecting and executing computational steps to optimize performance. The core mechanism centers around a self-learning process, wherein the algorithm analyzes the system's dynamics and adjusts its operational parameters. This approach aims to surpass the limitations of static algorithms by enabling a more responsive and adaptive computational paradigm. We present a preliminary model demonstrating the potential benefits of this adaptive strategy, focusing on a specific quantum system and computational task.

Sep 3, 20260 citations

Quantum Information Entropy Encoding

Jincheng Zhang

Quantum information entropy represents a fundamental measure of uncertainty in a quantum system. Efficiently encoding and manipulating this entropy is crucial for various quantum algorithms and applications. This paper explores the development of a novel encoding scheme based on quantum entanglement, aiming to dynamically adjust the encoding strength based on the system's internal state. We propose a method utilizing the inherent self-adaptative properties of entangled states to achieve a more efficient and robust approach to quantum information processing. This work addresses the limitations of traditional encoding methods by introducing a mechanism for adaptive strength adjustment, minimizing redundancy and potentially unlocking new computational possibilities. The core mechanism centers around leveraging the entanglement to create a feedback loop that optimizes the encoding process. We detail the proposed algorithm, its underlying principles, and preliminary experimental validation demonstrating its effectiveness. The research focuses on the potential of this approach to significantly improve the performance of quantum information processing.

Sep 4, 20260 citations