Ultra-dense moving cascaded metasurface holography by using a physics-driven neural network

• DOI: 10.1364/oe.463104
• Publication Date: 2022-06-10T17:00:09Z
• Authors: Hongqiang Zhou; Xin Li; He Wang; Shifei Zhang; Zhaoxian Su; Qiang Jiang; Naqeeb Ullah; Xiaowei Li; Yongtian Wang; Lingling Huang
• Keywords: Holographic display; Camouflage; Ptychography

Metasurfaces are promising platforms for integrated compact optical systems. Traditional metasurface holography design algorithms limited to information capacity due finite spatial bandwidth production, which is insufficient the growing demand big data storage and encryption. Here, we propose demonstrate deep learning empowered ultra-dense complex-amplitude using step-moving cascaded metasurfaces. Using artificial intelligence optimization strategy, barriers of traditional can be conquered meet diverse practical requirements. Two metasurfaces form desired holography. One them move switch reconstruction images diffraction propagation accumulated during path. The pattern from first propagates at a different distance meets with second metasurface, reconstructing target holographic reconstructions in far-field. Such technique provide new solution multi-dimensional beam shaping, encryption, camouflage, on-chip ultra-high-density storage, etc.