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Wavelength-multiplexed massively parallel diffractive optical information storage and image projection

arXiv 2604.02624 ↗First posted 3 Apr 2026physics.optics cs.CV cs.NEcited by 0

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Abstract (arXiv)

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.

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18 of 59 references.

References · 18

  1. 2018All-Optical Machine Learning Using Diffractive Deep Neural Networkscited by 177
  2. 2020Misalignment Resilient Diffractive Optical Networkscited by 33
  3. 2019Design of Task-Specific Optical Systems Using Broadband Diffractive Neural Networkscited by 27
  4. 2021All-Optical Synthesis of an Arbitrary Linear Transformation Using Diffractive Surfacescited by 24
  5. 2022Diffractive all-optical computing for quantitative phase imagingcited by 22
  6. 2022To image, or not to image: Class-specific diffractive cameras with all-optical erasure of undesired objectscited by 21
  7. 2022Snapshot Multispectral Imaging Using a Diffractive Optical Networkcited by 16
  8. 2022Data class-specific all-optical transformations and encryptioncited by 16
  9. 2023Quantitative phase imaging (QPI) through random diffusers using a diffractive optical networkcited by 10
  10. 2023Multispectral Quantitative Phase Imaging Using a Diffractive Optical Networkcited by 10
  11. 2023Universal Polarization Transformations: Spatial programming of polarization scattering matrices using a deep learning-designed diffractive polarization transformercited by 8
  12. 2023All-Optical Phase Conjugation Using Diffractive Wavefront Processingcited by 8
6 more
  1. 2024Optical Generative Modelscited by 8
  2. 2025Model-free front-to-end training of a large high performance laser neural networkcited by 4
  3. 2020All-Optical Information Processing Capacity of Diffractive Surfacescited by 3
  4. 2024Subwavelength Imaging using a Solid-Immersion Diffractive Optical Processorcited by 2
  5. 2024Multiplane Quantitative Phase Imaging Using a Wavelength-Multiplexed Diffractive Optical Processorcited by 2
  6. 2025Model-free Optical Processors using In Situ Reinforcement Learning with Proximal Policy Optimizationcited by 2

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