A Quantum String‐Matching Algorithm
A novel quantum algorithm for string‐matching is introduced that significantly enhances the complexity of this fundamental operation, essential in numerous computing applications. The algorithm is designed as a composite quantum denoising procedure applied to a quantum‐generated dot‐matrix plot, whi...
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| Veröffentlicht in: | Advanced quantum technologies (Online) Jg. 8; H. 3 |
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| Sprache: | Englisch |
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01.03.2025
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| Abstract | A novel quantum algorithm for string‐matching is introduced that significantly enhances the complexity of this fundamental operation, essential in numerous computing applications. The algorithm is designed as a composite quantum denoising procedure applied to a quantum‐generated dot‐matrix plot, which is treated as an image. This approach effectively identifies regions of similarity between two input strings of lengths N and M. For strings of equal length, the algorithm achieves a time complexity of O(N+log(N)+6N2)$O( {N + log( N ) + 6{{N}^2}} )$ and a space complexity of O(log(2N))$O( {log( {2N} )} )$, demonstrating a clear advantage in quantum computational efficiency.
A string‐matching quantum algorithm is introduced, offering significant improvements in computational complexity. The algorithm employs a quantum image denoising method applied to a quantum‐generated dot‐matrix plot view, to identify regions of similarity between two input strings of lengths N and M. For strings of equal length, the algorithm achieves an improved time complexity of O(N+log(N)+6N2)$O( {N + log( N ) + 6{{N}^2}} )$ and space complexity of O(log(2N))$O( {log( {2N} )} )$. |
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| AbstractList | A novel quantum algorithm for string‐matching is introduced that significantly enhances the complexity of this fundamental operation, essential in numerous computing applications. The algorithm is designed as a composite quantum denoising procedure applied to a quantum‐generated dot‐matrix plot, which is treated as an image. This approach effectively identifies regions of similarity between two input strings of lengths N and M. For strings of equal length, the algorithm achieves a time complexity of O(N+log(N)+6N2)$O( {N + log( N ) + 6{{N}^2}} )$ and a space complexity of O(log(2N))$O( {log( {2N} )} )$, demonstrating a clear advantage in quantum computational efficiency.
A string‐matching quantum algorithm is introduced, offering significant improvements in computational complexity. The algorithm employs a quantum image denoising method applied to a quantum‐generated dot‐matrix plot view, to identify regions of similarity between two input strings of lengths N and M. For strings of equal length, the algorithm achieves an improved time complexity of O(N+log(N)+6N2)$O( {N + log( N ) + 6{{N}^2}} )$ and space complexity of O(log(2N))$O( {log( {2N} )} )$. |
| Author | Prousalis, Konstantinos Konofaos, Nikos Kydros, Asimakis |
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| Snippet | A novel quantum algorithm for string‐matching is introduced that significantly enhances the complexity of this fundamental operation, essential in numerous... |
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| SubjectTerms | quantum algorithm quantum dot‐matrix plot quantum image noise filtering quantum line pattern extraction quantum string searching |
| Title | A Quantum String‐Matching Algorithm |
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