Ising machine based on charge re-distribution

Ising machines have attracted significant attention for solving quadratic unconstrained binary optimization (QUBO) with high performance. Among them, CMOS-compatible dynamics-based designs are promising approaches with high efficiency, scalability, and potential extension to more general combinatorial optimization problems (COPs) beyond QUBO problems. However, these machines can be limited by poor solution quality due to variations and leakage, or by long solution times resulting from inefficient annealing. In this paper, we propose a novel all-to-all connected Ising machine based on charge redistribution, capable of solving generic QUBO problems. To enhance solution quality, we apply a stochastic cycling annealing technique. A 50-spin Ising machine was developed using commercial 65nm CMOS technology, with both system-level and circuit-level designs implemented. Additionally, behavior-level simulations were conducted to evaluate the performance of a larger system. Simulation results show that the proposed Ising machine delivers competitive solution quality with reduced time-to-solution, making it a strong candidate for solving COPs.

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Publication Details

Published
2025-05-25
DOI
https://doi.org/10.1109/iscas56072.2025.11044217
Citations
1
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
2.48
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article

Ising machine based on charge re-distribution

Matthew K. Burns, Yongchao Liu, Michael Huang, Hui Wu et al.
1 citations
Neural Networks and Applications
2.48
article

Ising machine based on charge re-distribution

Matthew K. Burns, Yongchao Liu, Michael Huang, Hui Wu, L. C. Sun
article en
1 citations

Abstract

Ising machines have attracted significant attention for solving quadratic unconstrained binary optimization (QUBO) with high performance. Among them, CMOS-compatible dynamics-based designs are promising approaches with high efficiency, scalability, and potential extension to more general combinatorial optimization problems (COPs) beyond QUBO problems. However, these machines can be limited by poor solution quality due to variations and leakage, or by long solution times resulting from inefficient annealing. In this paper, we propose a novel all-to-all connected Ising machine based on charge redistribution, capable of solving generic QUBO problems. To enhance solution quality, we apply a stochastic cycling annealing technique. A 50-spin Ising machine was developed using commercial 65nm CMOS technology, with both system-level and circuit-level designs implemented. Additionally, behavior-level simulations were conducted to evaluate the performance of a larger system. Simulation results show that the proposed Ising machine delivers competitive solution quality with reduced time-to-solution, making it a strong candidate for solving COPs.

University of Rochester (US)
Openalex Percentile: Top 10%
Neural Networks and Applications
2.48
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Ising machine based on charge re-distribution — Matthew K. Burns, Yongchao Liu, et al. · (2025) | TGRS Research Map | TGRS