# Towards Evolutionary Optimization Using the Ising Model

arXiv: https://arxiv.org/abs/2511.15377 · HTML: https://mlsanity.com/paper/2511.15377/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Nov 2025.

## Built on by (most cited first, 1 of 1)

- [Unsupervised Symbolic Anomaly Detection](https://mlsanity.com/paper/2603.17575/) (2026)

## Abstract (arXiv)

In this paper, we study the problem of finding the global minima of a given function. Specifically, we consider complicated functions with numerous local minima, as is often the case for real-world data mining losses. We do so by applying a model from theoretical physics to create an Ising model-based evolutionary optimization algorithm. Our algorithm creates stable regions of local optima and a high potential for improvement between these regions. This enables the accurate identification of global minima, surpassing comparable methods, and has promising applications to ensembles.