Adaptive Quantum Graph Computation

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces an adaptive quantum graph computation framework designed to tackle complex graph problems by leveraging the unique properties of quantum graphs. We propose a novel algorithm that dynamically adjusts the quantum circuit parameters based on the graph's structure, enabling efficient and accurate computation and optimization. The core mechanism involves simulating graph behavior, predicting structural and property relationships, and iteratively refining the quantum circuit to achieve optimal results. This approach offers a significant advancement over traditional methods, particularly for large and intricate graphs. The paper details the framework's architecture, the implemented quantum circuit design, and the resulting performance improvements through simulations.

DOI: 10.5281/zenodo.22203809

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