A quantum-inspired probabilistic prime factorization based on virtually connected Boltzmann machine and probabilistic annealing

Hyundo Jung, Hyunjin Kim, Woojin Lee, Jinwoo Jeon, Yohan Choi, Taehyeong Park, Chulwoo Kim

Research output: Contribution to journalArticlepeer-review

Abstract

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 × 108 times improvement in the number of sampling operations compared with previous factorization machines, with a 22-fold smaller hardware resource.

Original languageEnglish
Article number16186
JournalScientific reports
Volume13
Issue number1
DOIs
Publication statusPublished - 2023 Dec

Bibliographical note

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© 2023, Springer Nature Limited.

ASJC Scopus subject areas

  • General

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