Encoding independent wavefronts in a single metasurface for high-order optical vortex recognition.

Area of Science:

• Optics and Photonics
• Metamaterials
• Optical Communications

Background:

• Orbital angular momentum (OAM) in vortex beams offers high communication confidentiality and low crosstalk.
• Existing OAM pattern recognition often relies on complex AI models requiring large datasets.
• A need exists for efficient and compact OAM recognition mechanisms for advanced optical communication systems.

Purpose of the Study:

• To develop a passive, all-dielectric metasurface for recognizing high-order optical vortex beams.
• To demonstrate a metasurface-based OAM pattern recognition mechanism that avoids AI models.
• To enable simultaneous encoding of wavefront and transmission paths for OAM beam identification.

Main Methods:

• A single passive all-dielectric metasurface composed of TiO2 nanopillars on a SiO2 substrate was designed and fabricated.
• The metasurface was engineered to simultaneously encode wavefront and transmission paths for incident OAM beams.
• Spin angular momentum (SAM) was utilized to spatially separate vortex beams after transmission through the metasurface.

Main Results:

• The metasurface successfully demonstrated OAM pattern recognition for high-order optical vortexes.
• A proof-of-concept metasurface with 14 signal channels was constructed, with 12 channels configurable for detecting predefined topological charges.
• The device effectively separates vortex beams based on their OAM and SAM properties.

Conclusions:

• Metasurfaces provide an effective platform for OAM pattern recognition, bypassing the need for large AI datasets.
• The proposed device enables miniaturization of optical vortex communication systems and advanced OAM detection technologies.
• This work paves the way for more sophisticated and compact OAM-based communication and sensing applications.