Recovering topological information of light by topological learning
The evolution of modern-day communication networks towards optical solutions with enhanced capacity and robustness is driving interest in topological light waves, exploiting their stability against perturbations through a topological invariant, e.g., the skyrmion number. However, detecting the underlying topology remains a computationally intense process even under ideal conditions, becoming intractable after passing through strongly disordered channels, where the degradation into unrecognisable speckle appears to destroy the topology. Here, we propose and demonstrate a topology-enhanced artificial intelligence (AI) approach to recover and classify such apparently lost topological informa...
| Authors | Benquan Wang, Trishita Das, Yuhan Peng et al. |
|---|---|
| Primary category | physics.optics |
| Published | 6 September 2026 |
| Last updated at source | 6 September 2026 |
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