Self-Adaptive Topological Geometry Quantum Mapping Validation

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper investigates the application of self-adaptive geometric topology to quantum mapping validation, addressing the challenges of instability and computational inefficiency in traditional methods. We introduce a novel framework that dynamically adjusts key parameters during the mapping process, enabling automated parameter tuning and ultimately improving the stability and efficiency of the resulting maps. The core mechanism involves a dynamically evolving geometric topology representation that serves as a constraint and guide for the quantum mapping process. We present a theoretical framework and demonstrate its efficacy through simulations, demonstrating a significant improvement in mapping stability and computational speed compared to existing approaches.

DOI: 10.5281/zenodo.22297869

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