基于自适应几何的量子态生成

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel quantum state generation technique based on adaptive geometry, leveraging the inherent properties of quantum geometry to produce quantum states with predefined characteristics and controlled manipulation. Traditional approaches rely on manual design, limiting the potential for generating tailored states. This work proposes a method that utilizes the self-relevant nature of quantum geometry to automate the creation of quantum states, offering a significant advancement in state generation capabilities. The core mechanism involves the design of self-adaptive quantum state generators, enabling precise control and guiding of generated states. This research explores the potential of this approach to overcome limitations of existing methods and opens avenues for more versatile and controllable quantum systems.

DOI: 10.5281/zenodo.22184928

Related papers

Self-Adaptive Geometric Field Theory for Quantum State Generation

Jincheng Zhang

This paper presents a novel approach to quantum state generation leveraging the principles of self-adaptive geometric field theory. Traditional methods often rely on deterministic classical approaches, limiting the potential for nuanced and precisely controlled quantum states. We propose a framework that dynamically adjusts geometric parameters to mimic the evolution of quantum systems, offering unprecedented control and adaptability in generating specific quantum states. The core mechanism focuses on utilizing geometric fields to represent and evolve quantum states, enabling a fundamentally different approach to state creation. This research explores the potential of this technique to overcome limitations inherent in conventional quantum state generation, leading to new opportunities in quantum simulation and information processing. The investigation will detail the design of a self-adaptive geometric field theory, its implementation, and preliminary results demonstrating the capability to generate complex quantum states.

Aug 31, 20260 citations

基于自适应拓扑的量子态生成算法

Jincheng Zhang

This paper introduces a novel quantum state generation algorithm based on adaptive topology. Traditional quantum state generation methods often rely on manual design, lacking the ability for automatic learning. Our algorithm leverages the power of topological structures to efficiently generate specific quantum states, offering enhanced capabilities for quantum computing optimization and control. This approach overcomes limitations of existing techniques by providing a dynamically constructed state space that can be tailored for specific computational tasks. We present a framework for generating and manipulating quantum states utilizing adaptive topology, demonstrating its potential for significant improvements in quantum algorithm performance. The core mechanism involves constructing a topological structure that guides the creation of desired quantum states, with a focus on practical applications within quantum computing.

Sep 4, 20260 citations

基于自适应几何结构的量子算法

Jincheng Zhang

This paper introduces a novel quantum algorithm based on adaptive geometric structures, designed to optimize quantum computations by dynamically adjusting quantum system configurations. Traditional quantum algorithms often rely on predefined structures, limiting their versatility and potential for optimization. This algorithm utilizes adaptive geometry to dynamically adjust quantum systems, allowing for a more flexible and efficient approach to quantum problem-solving. The core mechanism involves the creation and manipulation of a dynamic geometric structure that responds to input data, enabling a tailored quantum system to be constructed. This approach offers a significant departure from existing methods, promising enhanced performance and adaptability in quantum computation.

Sep 3, 20260 citations

基于自适应量子态的自适应拓扑控制

Jincheng Zhang

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.

Sep 3, 20260 citations

Core Claim: Develop a method based on adaptive quantum state geometry that automatically adjusts the geometric deformation of quantum states, enabling precise control, particularly in the handling of quantum state evolution.

Jincheng Zhang

Quantum state geometry offers a powerful framework for controlling and manipulating quantum systems, and the ability to dynamically adjust geometric parameters is crucial for achieving precise operations. This paper presents a novel algorithm for quantum state geometry, leveraging adaptive geometry to automatically adjust the shape of quantum states. We introduce a self-adaptive geometric deformation module that learns from the quantum state's characteristics, enabling precise control and efficient handling of complex quantum state evolution. The proposed approach offers a significant advancement over existing methods, particularly in scenarios requiring dynamic geometric adjustments. This work focuses on the development of a method that dynamically adjusts geometric parameters during quantum state evolution, leading to improved control and a more robust framework for quantum system manipulation. The core mechanism involves a self-learning module that adapts geometric parameters based on the quantum state's inherent properties, addressing a key challenge in precise quantum state engineering.

Aug 31, 20260 citations

基于自适应的量子态的生成与控制

Jincheng Zhang

This paper investigates a novel approach to quantum state generation and control, leveraging adaptive parameter adjustment to dynamically tailor quantum states. Traditional quantum computing methods often rely on fixed parameters, limiting the system's versatility. Our work proposes a system that adjusts quantum state parameters based on input data, enabling more flexible and efficient quantum computation. This design incorporates a self-adaptive control mechanism to achieve this dynamic state evolution. The core claim of this paper is that the proposed method offers a significant improvement in terms of adaptability and computational efficiency compared to existing approaches. This paper details the design of the adaptive control system, explores its performance through simulations, and discusses potential future directions. Keywords: Quantum State, Adaptive Control, Quantum Computation, Self-Adaptation, Quantum Algorithm.

Sep 3, 20260 citations