# IonQ preprint reports radar change-detection gains on quantum hardware

_Published Friday, September 25, 2026 at 2:21 AM EDT · Science · Latest · Tier 2 — Notable_

![IonQ preprint reports radar change-detection gains on quantum hardware — Primary](https://quantumcomputingreport.com/wp-content/uploads/2026/09/image-304.png)

IonQ researchers report that a quantum model detected changes in satellite radar images more accurately than two classical methods on a test dataset. In an arXiv preprint, they describe running training and inference on a 20-qubit trapped-ion processor. On unsmoothed images of Marine Corps Air Station Miramar, the hardware run reached a filtered F1 score of 0.37, compared with 0.24 and 0.16 for the classical baselines.

The model generates reference samples from pairs of radar images to estimate a background for change detection without smoothing away fine detail. On a separate volcanic-lava dataset, it matched the classical peak score of approximately 0.66 rather than exceeding it.

## Sources

- [quantumcomputingreport.com](https://quantumcomputingreport.com/ionq-demonstrates-quantum-generative-modeling-advantage-for-high-resolution-satellite-radar-change-detection/)

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Canonical: https://techandbusiness.org/newswire/aShL1wI2ICrHOps89GBgjv
Published: 2026-09-25T06:21:39.552Z
Story chronology: 2026-09-24T00:00:00.000Z
Retrieved: 2026-09-25T07:47:03.945Z
Publisher: Tech & Business (techandbusiness.org)