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基于动态量子态的相变理论

Jincheng Zhang

Published Sep 2, 2026• 0 citations
Publisher

Abstract

This paper presents a novel theoretical framework for quantum state evolution, termed the Dynamic Quantum State Theory (DQST). We establish a dynamic state evolution model, demonstrating the ability to analyze quantum state transitions and leverage these transitions for controlled quantum device operation. The core of this theory lies in the design of an automated control mechanism predicated on the observed dynamics of the quantum state. This approach offers a potential pathway toward achieving "self-adaptive" control of quantum devices, representing a significant advance over traditional approaches. The paper outlines the model's key components, explains the underlying mathematical principles, and provides a preliminary analysis of its capabilities. We demonstrate through simplified examples how the DQST framework can be used to model and control quantum transitions, highlighting its potential for advanced quantum control. The proposed mechanism is presented as a key differentiator, offering a fundamentally different approach to quantum device optimization.

DOI
10.5281/zenodo.22253562

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Quantum state transitions are a fundamental aspect of quantum mechanics, driving the evolution of quantum states and enabling quantum algorithms. This paper presents a novel framework for quantum computing based on the dynamic changes in quantum states, aiming to automate the execution of complex algorithms. We propose a self-adaptive quantum computing framework leveraging these transitions to achieve enhanced computational capabilities. The core mechanism centers around the controlled manipulation of quantum states through continuous transitions, allowing for automated optimization of quantum circuits. This approach contrasts with traditional quantum computing methods which often rely on pre-defined gate sequences. We demonstrate the framework's potential through a simplified, illustrative example of a quantum algorithm. The paper concludes with a discussion of future research directions and potential applications.
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Quantum state manipulation offers a paradigm shift in computational capabilities, particularly in complex quantum systems. Traditional methods often struggle with the inherent complexities of manipulating quantum states, demanding significant computational resources. This paper proposes a novel approach utilizing adaptive quantum state control – a system that dynamically adjusts the underlying quantum state to optimize control and efficiency. We introduce a novel algorithm based on self-adapting parameters, allowing for automated and highly efficient control of quantum states. This research addresses the limitations of existing techniques by introducing a mechanism for continuous parameter adjustment, paving the way for more effective quantum operations. The core focus is on achieving superior control and computational efficiency through the intelligent manipulation of quantum states. This work demonstrates the feasibility and potential of this approach, offering a significant advancement in the field of quantum state manipulation.
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