降低测量反馈型伊辛机对超参数的敏感性，提升实际可用性。
Reducing hyperparameter sensitivity in measurement-feedback based Ising machines
- 提出新方法减少测量反馈架构对超参数的依赖
- 实验验证可显著扩大有效超参数范围
- 适合硬件优化与实际部署场景的研究者
模拟伊辛机被视作组合优化问题的启发式硬件求解器，其性能潜力取决于超参数的精细调优。尽管其动态过程通常以连续时间模型描述，但多数实验实现采用离散时间的测量反馈架构。我们发现，在此类设置中，有效超参数的范围远小于理想连续模型下的情况。本文分析了这一差异及其对伊辛机实际运行的影响，并提出并实验验证了一种降低测量反馈架构对超参数选择敏感性的方法。
原文摘要 · Abstract (English)
Analog Ising machines have been proposed as heuristic hardware solvers for combinatorial optimization problems, with the potential to outperform conventional approaches, provided that their hyperparameters are carefully tuned. Their temporal evolution is often described using time-continuous dynamics. However, most experimental implementations rely on measurement-feedback architectures that operate in a time-discrete manner. We observe that in such setups, the range of effective hyperparameters is substantially smaller than in the envisioned time-continuous analog Ising machine. In this paper, we analyze this discrepancy and discuss its impact on the practical operation of Ising machines. Next, we propose and experimentally verify a method to reduce the sensitivity to hyperparameter selection of these measurement-feedback architectures.
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