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A quantum-inspired probabilistic prime factorization based on virtually connected Boltzmann machine and probabilistic annealing
Probabilistic computing has been introduced to operate functional networks using a probabilistic bit (p-bit), broadening the computational abilities in non-deterministic polynomial searching operations. However, previous developments have focused on emulating the operation of quantum computers simil...
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/PMC10533543/ https://www.ncbi.nlm.nih.gov/pubmed/37758803 http://dx.doi.org/10.1038/s41598-023-43054-5 |
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author | Jung, Hyundo Kim, Hyunjin Lee, Woojin Jeon, Jinwoo Choi, Yohan Park, Taehyeong Kim, Chulwoo |
author_facet | Jung, Hyundo Kim, Hyunjin Lee, Woojin Jeon, Jinwoo Choi, Yohan Park, Taehyeong Kim, Chulwoo |
author_sort | Jung, Hyundo |
collection | PubMed |
description | Probabilistic computing has been introduced to operate functional networks using a probabilistic bit (p-bit), broadening the computational abilities in non-deterministic polynomial searching operations. However, previous developments have focused on emulating the operation of quantum computers similarly, implementing every p-bit with large weight-sum matrix multiplication blocks and requiring tens of times more p-bits than semiprime bits. In addition, operations based on a conventional simulated annealing scheme required a large number of sampling operations, which deteriorated the performance of the Ising machines. Here we introduce a prime factorization machine with a virtually connected Boltzmann machine and probabilistic annealing method, which are designed to reduce the hardware complexity and number of sampling operations. From 10-bit to 64-bit prime factorizations were performed, and the machine offers up to 1.2 × 10(8) times improvement in the number of sampling operations compared with previous factorization machines, with a 22-fold smaller hardware resource. |
format | Online Article Text |
id | pubmed-10533543 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105335432023-09-29 A quantum-inspired probabilistic prime factorization based on virtually connected Boltzmann machine and probabilistic annealing Jung, Hyundo Kim, Hyunjin Lee, Woojin Jeon, Jinwoo Choi, Yohan Park, Taehyeong Kim, Chulwoo Sci Rep Article Probabilistic computing has been introduced to operate functional networks using a probabilistic bit (p-bit), broadening the computational abilities in non-deterministic polynomial searching operations. However, previous developments have focused on emulating the operation of quantum computers similarly, implementing every p-bit with large weight-sum matrix multiplication blocks and requiring tens of times more p-bits than semiprime bits. In addition, operations based on a conventional simulated annealing scheme required a large number of sampling operations, which deteriorated the performance of the Ising machines. Here we introduce a prime factorization machine with a virtually connected Boltzmann machine and probabilistic annealing method, which are designed to reduce the hardware complexity and number of sampling operations. From 10-bit to 64-bit prime factorizations were performed, and the machine offers up to 1.2 × 10(8) times improvement in the number of sampling operations compared with previous factorization machines, with a 22-fold smaller hardware resource. Nature Publishing Group UK 2023-09-27 /pmc/articles/PMC10533543/ /pubmed/37758803 http://dx.doi.org/10.1038/s41598-023-43054-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Jung, Hyundo Kim, Hyunjin Lee, Woojin Jeon, Jinwoo Choi, Yohan Park, Taehyeong Kim, Chulwoo A quantum-inspired probabilistic prime factorization based on virtually connected Boltzmann machine and probabilistic annealing |
title | A quantum-inspired probabilistic prime factorization based on virtually connected Boltzmann machine and probabilistic annealing |
title_full | A quantum-inspired probabilistic prime factorization based on virtually connected Boltzmann machine and probabilistic annealing |
title_fullStr | A quantum-inspired probabilistic prime factorization based on virtually connected Boltzmann machine and probabilistic annealing |
title_full_unstemmed | A quantum-inspired probabilistic prime factorization based on virtually connected Boltzmann machine and probabilistic annealing |
title_short | A quantum-inspired probabilistic prime factorization based on virtually connected Boltzmann machine and probabilistic annealing |
title_sort | quantum-inspired probabilistic prime factorization based on virtually connected boltzmann machine and probabilistic annealing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10533543/ https://www.ncbi.nlm.nih.gov/pubmed/37758803 http://dx.doi.org/10.1038/s41598-023-43054-5 |
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