Year: 2025
Type: article
Abstract: Polynomial multiplication is a fundamental operation in various fields of science and engineering. This paper proposes a quantum algorithm for polynomial multiplication that achieves improved efficiency over classical approaches. The core innovation is the use of a quantum Fourier transform with digital encoding. The practical utility and versatility of this algorithm are highlighted through its application to several related computational problems, including string matching, Toeplitz matrix-vector multiplication, and matrix decomposition algorithm. Furthermore, an enhanced version of the quantum polynomial multiplication algorithm is introduced, offering improvements in both execution process and time complexity.
Source: EPJ Quantum Technology
Authors: Shang Gao, Rui-Chen Huang, Bing-Xin Liu, Zhen-Wen Cheng, Hong-Lin Xie, Zhong-Xiang Zhang, Zhao-Qian Zhang, Guang-Bao Xu, Yu-Guang Yang
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,190
Awards: G1151905201, G4652247328
OpenAlex ID: W4415248147