We introduce a wavelength-multiplexed massively parallel diffractive information storage platform composed of dielectric surfaces that are structurally optimized at the wavelength scale using deep learning to store and project thousands of distinct image patterns, each assigned to a unique wavelength. Through numerical simulations in the visible spectrum, we demonstrated that our wavelength-multiplexed diffractive system can store and project over 4,000 independent desired images/patterns within its output field-of-view, with high image quality and minimal crosstalk between spectral channels. Furthermore, in a proof-of-concept experiment, we demonstrated a two-layer diffractive design that stored six distinct patterns and projected them onto the same output field of view at six different wavelengths (500, 548, 596, 644, 692, and 740 nm). This diffractive architecture is scalable and can operate at various parts of the electromagnetic spectrum without the need for material dispersion engineering or redesigning its optimized diffractive layers. The demonstrated storage capacity, reconstruction image fidelity, and wavelength-encoded massively parallel read-out of our diffractive platform offer a compact and fast-access solution for large-scale optical information storage, image projection applications.

翻译：我们提出了一种波长复用的大规模并行衍射信息存储平台，该平台由介电表面构成，利用深度学习在波长尺度上对结构进行优化，以存储和投影数千个不同的图像模式，每个模式对应一个独特的波长。通过在可见光谱中的数值模拟，我们证明该波长复用衍射系统能够在其输出视场内存储并投影超过4000个独立的目标图像/模式，具有高图像质量和极小的光谱通道间串扰。此外，在概念验证实验中，我们展示了一种双层衍射设计，该设计存储了六个不同的模式，并在六个不同波长（500、548、596、644、692和740 nm）下将其投影到同一输出视场中。这种衍射架构具有可扩展性，可在电磁波谱的各部分工作，无需进行材料色散工程或重新设计其优化的衍射层。该衍射平台所展示的存储容量、重建图像保真度以及波长编码的大规模并行读出能力，为大容量光学信息存储和图像投影应用提供了一种紧凑且快速访问的解决方案。