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

Published Aug 31, 2026• 0 citations

Abstract

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.

DOI: 10.5281/zenodo.22201236

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