Advancing quantum imaging through learning theory
Yunkai Wang, Changhun Oh, Junyu Liu, Liang Jiang, Sisi Zhou · 2025
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Description
Yunkai Wang and four co-authors advanced in 2025 the theory of quantum imaging by treating the camera itself as a learning machine. Their framework asks which features of a scene a physical device can estimate well, and how many samples each feature needs. Two tasks get the treatment: ordinary imaging and super-resolution of tiny sources.
An upgraded method separates several close sources that older techniques blurred into one, relaxing a strict assumption the field had leaned on. Sharper quantum cameras could matter wherever light is scarce, from microscopes watching single molecules to telescopes splitting twin stars.
Catalog record
| CREATOR | Yunkai Wang, Changhun Oh, Junyu Liu, Liang Jiang, Sisi Zhou |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 91 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |