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Biomolecular and quantum algorithms for the dominating set problem in arbitrary networks
A dominating set of a graph [Formula: see text] is a subset U of its vertices V, such that any vertex of G is either in U, or has a neighbor in U. The dominating-set problem is to find a minimum dominating set in G. Dominating sets are of critical importance for various types of networks/graphs, and...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10015031/ https://www.ncbi.nlm.nih.gov/pubmed/36918570 http://dx.doi.org/10.1038/s41598-023-30600-4 |
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author | Wong, Renata Chang, Weng-Long Chung, Wen-Yu Vasilakos, Athanasios V. |
author_facet | Wong, Renata Chang, Weng-Long Chung, Wen-Yu Vasilakos, Athanasios V. |
author_sort | Wong, Renata |
collection | PubMed |
description | A dominating set of a graph [Formula: see text] is a subset U of its vertices V, such that any vertex of G is either in U, or has a neighbor in U. The dominating-set problem is to find a minimum dominating set in G. Dominating sets are of critical importance for various types of networks/graphs, and find therefore potential applications in many fields. Particularly, in the area of communication, dominating sets are prominently used in the efficient organization of large-scale wireless ad hoc and sensor networks. However, the dominating set problem is also a hard optimization problem and thus currently is not efficiently solvable on classical computers. Here, we propose a biomolecular and a quantum algorithm for this problem, where the quantum algorithm provides a quadratic speedup over any classical algorithm. We show that the dominating set problem can be solved in [Formula: see text] queries by our proposed quantum algorithm, where n is the number of vertices in G. We also demonstrate that our quantum algorithm is the best known procedure to date for this problem. We confirm the correctness of our algorithm by executing it on IBM Quantum’s qasm simulator and the Brooklyn superconducting quantum device. And lastly, we show that molecular solutions obtained from solving the dominating set problem are represented in terms of a unit vector in a finite-dimensional Hilbert space. |
format | Online Article Text |
id | pubmed-10015031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100150312023-03-16 Biomolecular and quantum algorithms for the dominating set problem in arbitrary networks Wong, Renata Chang, Weng-Long Chung, Wen-Yu Vasilakos, Athanasios V. Sci Rep Article A dominating set of a graph [Formula: see text] is a subset U of its vertices V, such that any vertex of G is either in U, or has a neighbor in U. The dominating-set problem is to find a minimum dominating set in G. Dominating sets are of critical importance for various types of networks/graphs, and find therefore potential applications in many fields. Particularly, in the area of communication, dominating sets are prominently used in the efficient organization of large-scale wireless ad hoc and sensor networks. However, the dominating set problem is also a hard optimization problem and thus currently is not efficiently solvable on classical computers. Here, we propose a biomolecular and a quantum algorithm for this problem, where the quantum algorithm provides a quadratic speedup over any classical algorithm. We show that the dominating set problem can be solved in [Formula: see text] queries by our proposed quantum algorithm, where n is the number of vertices in G. We also demonstrate that our quantum algorithm is the best known procedure to date for this problem. We confirm the correctness of our algorithm by executing it on IBM Quantum’s qasm simulator and the Brooklyn superconducting quantum device. And lastly, we show that molecular solutions obtained from solving the dominating set problem are represented in terms of a unit vector in a finite-dimensional Hilbert space. Nature Publishing Group UK 2023-03-14 /pmc/articles/PMC10015031/ /pubmed/36918570 http://dx.doi.org/10.1038/s41598-023-30600-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wong, Renata Chang, Weng-Long Chung, Wen-Yu Vasilakos, Athanasios V. Biomolecular and quantum algorithms for the dominating set problem in arbitrary networks |
title | Biomolecular and quantum algorithms for the dominating set problem in arbitrary networks |
title_full | Biomolecular and quantum algorithms for the dominating set problem in arbitrary networks |
title_fullStr | Biomolecular and quantum algorithms for the dominating set problem in arbitrary networks |
title_full_unstemmed | Biomolecular and quantum algorithms for the dominating set problem in arbitrary networks |
title_short | Biomolecular and quantum algorithms for the dominating set problem in arbitrary networks |
title_sort | biomolecular and quantum algorithms for the dominating set problem in arbitrary networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10015031/ https://www.ncbi.nlm.nih.gov/pubmed/36918570 http://dx.doi.org/10.1038/s41598-023-30600-4 |
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