Han, Ki Hyuk Park, Gyuyoung Ahn, Jeong Ung Kim, Yongjin Yun, Deok Hyun Jang, Seung-Hun Nah, Young-Jun Kang, Min-Gu Koo, Hyun Cheol Lee, Oukjae 2025-08-31T01:30:16Z 2025-08-31T01:30:16Z 2025-08-27 2025-08 https://pubs.kist.re.kr/handle/201004/153059 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. English Nature Publishing Group Multi-level probabilistic computing: application to the multiway number partitioning problems Article 10.1038/s41598-025-14531-w 1 Scientific Reports, v.15 Scientific Reports 15 Y scie scopus 001546874300021 2-s2.0-105012749742 Multidisciplinary Sciences Science & Technology - Other Topics Article Probabilistic computing Combinatorial optimization problem Multiway number partitioning