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Topological optical differentiator.

Tengfeng ZhuCheng GuoJunyi HuangHaiwen WangMeir OrensteinZhichao RuanShanhui Fan
Published in: Nature communications (2021)
Optical computing holds significant promise of information processing with ultrahigh speed and low power consumption. Recent developments in nanophotonic structures have generated renewed interests due to the prospects of performing analog optical computing with compact devices. As one prominent example, spatial differentiation has been demonstrated with nanophotonic structures and directly applied for edge detection in image processing. However, broadband isotropic two-dimensional differentiation, which is required in most imaging processing applications, has not been experimentally demonstrated yet. Here, we establish a connection between two-dimensional optical spatial differentiation and a nontrivial topological charge in the optical transfer function. Based on this connection, we experimentally demonstrate an isotropic two-dimensional differentiation with a broad spectral bandwidth, by using the simplest photonic device, i.e. a single unpatterned interface. Our work indicates that exploiting concepts from topological photonics can lead to new opportunities in optical computing.
Keyphrases
  • high resolution
  • high speed
  • mass spectrometry
  • deep learning
  • machine learning
  • optical coherence tomography
  • big data
  • low cost