Scientific Reports

Multi-level probabilistic computing: application to the multiway number partitioning problems

Ki-Hyuk Han, G.S. Park, Jeong Ung Ahn, YongJin Kim, Deok Hyun Yun, Seung-Hun Jang, Young-Jun Nah, Min Gu Kang, Hyun Cheol Koo, OukJae Lee

Published Aug 7, 2025• 0 citations

Publisher

Abstract

Probabilistic computing, a class of physics-based computing, bridges the gap between quantum computing and the classical von Neumann architecture. This approach provides more efficient means of addressing NP problems, which are challenging for classical computers. In this work, we analyze the core concept of probabilistic computing which is based on the Ising model framework-including bit fluctuations and energy trends. In addition, we extend the traditional binary (two-level) system into a multi-level probabilistic framework, i.e. number partitioning problem to multiway number partitioning problem, as a case study.

DOI: 10.1038/s41598-025-14531-w

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