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-Classical Hybrid Dynamics

Jincheng Zhang

Published Sep 3, 2026• 0 citations
Publisher

Abstract

This paper investigates the development of a dynamic framework for quantum systems, explicitly modeling the interplay between quantum and classical behavior. We propose a 'hybrid' approach, leveraging a 'quantum-classical coherence matrix' to dynamically adjust quantum states in response to classical influences, effectively creating a continuous evolution. The core mechanism centers around maintaining a persistent, evolving state, bridging the gap between the deterministic nature of quantum mechanics and the often-ambiguous behavior of classical systems. The resulting model offers a novel perspective on complex systems, potentially facilitating a deeper understanding of phenomena like phase transitions, emergent behavior, and the limits of classical predictability. This research explores the potential of this framework for applications in quantum computing, materials science, and fundamental physics.

DOI
10.5281/zenodo.22279269

Related papers

Quantum Decoherence Control Theory and Dynamical Systems of Complex Systems

Jincheng Zhang

This paper explores the application of quantum decoherence theory to the control of complex classical systems. We propose a novel framework leveraging the probabilistic nature of decoherence to achieve precise control and prediction of complex system dynamics. The core mechanism involves stochastic control, where noise injection and coupling strength are optimized to steer the system towards a desired evolution path. Unlike traditional approaches to complex system analysis and control, this work introduces a fundamentally new perspective by translating core quantum concepts – specifically decoherence – into the domain of classical complexity. The theoretical development presents a method for managing and manipulating complex systems by understanding and mitigating the effects analogous to decoherence, offering potential advancements in fields ranging from chaos control to network dynamics. The central aim is to provide a robust and adaptable strategy for influencing the behavior of intricate systems, moving beyond purely deterministic models. ---

•Aug 28, 2026•0 citations

Quantum-Induced Phase Transitions in Dynamical Systems

Jincheng Zhang

Quantum-induced phase transitions (QIPTs) represent a fascinating and rapidly developing area of research in condensed matter physics and beyond. This paper explores the theoretical framework for understanding and predicting these transitions, leveraging the principles of quantum mechanics to reveal emergent behavior and provide a new perspective on complex system dynamics. We propose a model centered around quantum entanglement and superposition, aiming to bridge the gap between classical and quantum descriptions. The core mechanism involves simulating the evolution of a dynamical system using quantum algorithms, allowing us to identify and characterize the transition points and associated dynamics. The implications of this research extend to diverse fields, including materials science, cosmology, and even fundamental physics. This paper presents a detailed outline of the proposed model, including mathematical formalism and analysis of potential applications. The focus is on establishing a robust theoretical foundation, paving the way for future investigations into the underlying mechanisms driving QIPTs.

•Sep 6, 2026•0 citations

Quantum Information Dynamics

Jincheng Zhang

This research delves into the intersection of quantum information dynamics and complex systems, specifically focusing on the interplay between quantum entanglement and dynamical systems. We propose a novel framework that integrates these concepts to model potential quantum computation behaviors, moving beyond traditional algorithmic approaches. The core of this work centers on the conceptualization of a dynamic system evolution driven by quantum entanglement, providing a mechanism for understanding and potentially predicting the behavior of quantum algorithms. This investigation seeks to establish a robust model for exploring and analyzing the emergent properties of quantum systems through the lens of dynamic dynamics.

•Sep 6, 2026•0 citations

Quantum Simulation of Complex Material Behavior

Jincheng Zhang

Quantum simulation of complex material behavior represents a significant advancement in materials science, offering the potential to understand and predict emergent phenomena not achievable through traditional classical methods. This paper investigates a novel quantum simulation approach leveraging a hybrid quantum-classical framework to model the correlated dynamics of multiple interacting particles, focusing on a specifically designed representation of the quantum entanglement landscape. We propose a method that surpasses existing techniques by addressing the inherent challenges of simulating complex systems, particularly those exhibiting emergent behavior. The core claim is that this method will provide a more accurate and insightful understanding of material properties, opening avenues for designing novel materials with tailored functionalities.

•Aug 31, 2026•0 citations

Title: Quantum-Classical Convergence in Dynamical Systems

Jincheng Zhang

Quantum-Classical convergence describes the inevitable merging of quantum and classical systems, often observed in complex systems exhibiting chaotic behavior. This paper explores a novel mathematical framework for understanding this convergence, proposing a hybrid approach that integrates concepts from quantum mechanics (superposition, entanglement) and classical chaos theory. We introduce a model where classical elements are intrinsically influenced by quantum fluctuations, aiming to illuminate the dynamic interplay between these two fundamental scales. The paper details the core mechanism, outlining the integration of quantum and chaotic elements into a unified system. The resulting model offers a new perspective on the emergence of patterns and stability within complex dynamical systems, particularly in the context of chaotic systems. This work provides a foundation for advanced theoretical investigations into the fundamental principles underlying the convergence of these seemingly disparate realms.

•Aug 31, 2026•0 citations

Physics-Quantum Coupling Framework

Jincheng Zhang

This paper introduces a novel computational framework designed to bridge the gap between complex physical systems and quantum computation. The framework aims to facilitate the efficient exploration and solution of problems involving intricate systems by leveraging the unique capabilities of quantum mechanics. We present a system for seamlessly integrating physical models with quantum algorithms, optimizing for both computational speed and accuracy. The core mechanism centers around dynamically coupling physical and quantum components, employing quantum phenomena to accelerate computations and potentially unlock solutions inaccessible through classical methods. The paper details the framework's architecture, proposes a methodology for model-to-quantum algorithm mapping, and showcases its efficacy through illustrative examples. The motivation stems from the inherent limitations of classical computation in tackling complex systems, particularly those involving quantum phenomena, and highlights the potential of quantum-enhanced computation.

•Aug 31, 2026•0 citations
This paper investigates the development of a dynamic framework for quantum systems, explicitly modeling the interplay between quantum and classical behavior. We propose a 'hybrid' approach, leveraging a 'quantum-classical coherence matrix' to dynamically adjust quantum states in response to classical influences, effectively creating a continuous evolution. The core mechanism centers around maintaining a persistent, evolving state, bridging the gap between the deterministic nature of quantum mechanics and the often-ambiguous behavior of classical systems. The resulting model offers a novel perspective on complex systems, potentially facilitating a deeper understanding of phenomena like phase transitions, emergent behavior, and the limits of classical predictability. This research explores the potential of this framework for applications in quantum computing, materials science, and fundamental physics.
This paper explores the application of quantum decoherence theory to the control of complex classical systems. We propose a novel framework leveraging the probabilistic nature of decoherence to achieve precise control and prediction of complex system dynamics. The core mechanism involves stochastic control, where noise injection and coupling strength are optimized to steer the system towards a desired evolution path. Unlike traditional approaches to complex system analysis and control, this work introduces a fundamentally new perspective by translating core quantum concepts – specifically decoherence – into the domain of classical complexity. The theoretical development presents a method for managing and manipulating complex systems by understanding and mitigating the effects analogous to decoherence, offering potential advancements in fields ranging from chaos control to network dynamics. The central aim is to provide a robust and adaptable strategy for influencing the behavior of intricate systems, moving beyond purely deterministic models. ---
Quantum-induced phase transitions (QIPTs) represent a fascinating and rapidly developing area of research in condensed matter physics and beyond. This paper explores the theoretical framework for understanding and predicting these transitions, leveraging the principles of quantum mechanics to reveal emergent behavior and provide a new perspective on complex system dynamics. We propose a model centered around quantum entanglement and superposition, aiming to bridge the gap between classical and quantum descriptions. The core mechanism involves simulating the evolution of a dynamical system using quantum algorithms, allowing us to identify and characterize the transition points and associated dynamics. The implications of this research extend to diverse fields, including materials science, cosmology, and even fundamental physics. This paper presents a detailed outline of the proposed model, including mathematical formalism and analysis of potential applications. The focus is on establishing a robust theoretical foundation, paving the way for future investigations into the underlying mechanisms driving QIPTs.
This research delves into the intersection of quantum information dynamics and complex systems, specifically focusing on the interplay between quantum entanglement and dynamical systems. We propose a novel framework that integrates these concepts to model potential quantum computation behaviors, moving beyond traditional algorithmic approaches. The core of this work centers on the conceptualization of a dynamic system evolution driven by quantum entanglement, providing a mechanism for understanding and potentially predicting the behavior of quantum algorithms. This investigation seeks to establish a robust model for exploring and analyzing the emergent properties of quantum systems through the lens of dynamic dynamics.
Quantum simulation of complex material behavior represents a significant advancement in materials science, offering the potential to understand and predict emergent phenomena not achievable through traditional classical methods. This paper investigates a novel quantum simulation approach leveraging a hybrid quantum-classical framework to model the correlated dynamics of multiple interacting particles, focusing on a specifically designed representation of the quantum entanglement landscape. We propose a method that surpasses existing techniques by addressing the inherent challenges of simulating complex systems, particularly those exhibiting emergent behavior. The core claim is that this method will provide a more accurate and insightful understanding of material properties, opening avenues for designing novel materials with tailored functionalities.
Quantum-Classical convergence describes the inevitable merging of quantum and classical systems, often observed in complex systems exhibiting chaotic behavior. This paper explores a novel mathematical framework for understanding this convergence, proposing a hybrid approach that integrates concepts from quantum mechanics (superposition, entanglement) and classical chaos theory. We introduce a model where classical elements are intrinsically influenced by quantum fluctuations, aiming to illuminate the dynamic interplay between these two fundamental scales. The paper details the core mechanism, outlining the integration of quantum and chaotic elements into a unified system. The resulting model offers a new perspective on the emergence of patterns and stability within complex dynamical systems, particularly in the context of chaotic systems. This work provides a foundation for advanced theoretical investigations into the fundamental principles underlying the convergence of these seemingly disparate realms.
This paper introduces a novel computational framework designed to bridge the gap between complex physical systems and quantum computation. The framework aims to facilitate the efficient exploration and solution of problems involving intricate systems by leveraging the unique capabilities of quantum mechanics. We present a system for seamlessly integrating physical models with quantum algorithms, optimizing for both computational speed and accuracy. The core mechanism centers around dynamically coupling physical and quantum components, employing quantum phenomena to accelerate computations and potentially unlock solutions inaccessible through classical methods. The paper details the framework's architecture, proposes a methodology for model-to-quantum algorithm mapping, and showcases its efficacy through illustrative examples. The motivation stems from the inherent limitations of classical computation in tackling complex systems, particularly those involving quantum phenomena, and highlights the potential of quantum-enhanced computation.