ORIGINAL RESEARCH article
Front. Phys.
Sec. Quantum Engineering and Technology
Volume 13 - 2025 | doi: 10.3389/fphy.2025.1617637
This article is part of the Research TopicRecent Mathematical and Theoretical Progress in Quantum MechanicsView all articles
Quantum Walk Information Processing Algorithm for Grid Communication Networks
Provisionally accepted
- The University of Sydney, Darlington, Australia
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In response to the problem of slow processing speed and inability to ensure information security in traditional communication network information processing technology, this study combines quantum walk with convolutional neural networks to extract network information, encrypts the extracted network information by combining quantum roaming with compressive sensing, and proposes a quantum walk information processing algorithm for grid-based communication networks. The outcomes denoted that when the compression ratio was 0.25, the Peak Signal-to-Noise Ratio (PSNR) of the proposed information processing algorithm was 27.69, which increased by 6.34% and 36.61% respectively compared to the other two algorithms, proving that it can ensure the quality of information transmission. The quantum bit variation during key generation of the proposed information processing algorithm was 48.92 bits, which is higher than other algorithms. The space overhead was 8.3 KB, significantly lower than other algorithms, proving its good scalability and low overhead, which can effectively reduce costs. The quantum walk-based communication network information processing algorithm proposed by the research has superior performance, providing ideas for improving the efficiency and security of communication network information transmission.
Keywords: Grid-based communication network, quantum walk, Convolutional Neural Network, Compressive sensing, Information Processing
Received: 24 Apr 2025; Accepted: 13 Jun 2025.
Copyright: © 2025 Xia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Tianxing Xia, The University of Sydney, Darlington, Australia
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