# Reducing hyperparameter sensitivity in measurement-feedback based Ising machines

arXiv: https://arxiv.org/abs/2603.04093 · HTML: https://mlsanity.com/paper/2603.04093/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 28 references that are in the map.
- First posted on arXiv 4 Mar 2026.

## Builds on (most cited first, 1 of 1)

- [Ising formulations of many NP problems](https://mlsanity.com/paper/1302.5843/) (2013)

## Abstract (arXiv)

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.