Title: Adaptive Geometric Transformations for Quantum Computing

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum computing holds immense promise for revolutionizing various fields, from drug discovery to materials science. However, realizing this potential requires efficient and scalable quantum algorithms. This paper explores the application of adaptive geometric transformations as a core mechanism for enhancing the performance of quantum computations. We propose a novel algorithm that dynamically adjusts geometric parameters during the computation process, aiming to achieve higher fidelity and reduced computational complexity. The core claim is that this approach significantly improves the efficiency of quantum algorithms, particularly in scenarios involving complex quantum circuits. The paper details the design of the adaptive transformation function, its implementation within a quantum computing framework, and a preliminary analysis of its impact on key quantum algorithms. The study demonstrates the efficacy of this approach through simulations and a simplified demonstration of a specific quantum circuit. The research contributes to the ongoing development of robust and adaptable quantum algorithms.

DOI: 10.5281/zenodo.22280688

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