Aluminum-based plasmonic metasurface for computational spectrometry with full coverage of visible light.

Reconstructive spectrometers/spectral cameras have immense potential for portable applications in various fields, including environmental monitoring, biomedical research and diagnostics, and agriculture and food safety. However, the performance of these spectrometers/spectral cameras is severely limited by the operational bandwidth, spectral diversity, and angle sensitivity of the spectral modulation devices. In this work, we propose a compact spectrometer based on plasmonic metasurfaces that operate across the entire visible wavelength range, covering wavelengths from 400 to 750 nm.

Disordered metasurface enabled single-shot full-Stokes polarization imaging leveraging weak dichroism.

Polarization, one of the fundamental properties of light, is critical for certain imaging applications because it captures information from the scene that cannot directly be recorded by traditional intensity cameras. Currently, mainstream approaches for polarization imaging rely on strong dichroism of birefringent crystals or artificially fabricated structures that exhibit a high diattenuation typically exceeding 99%, which corresponds to a polarization extinction ratio (PER) >~100. This not only limits the transmission efficiency of light, but also makes them either offer narrow operational bandwidth or be non-responsive to the circular polarization.

Trilobite-inspired neural nanophotonic light-field camera with extreme depth-of-field.

A unique bifocal compound eye visual system found in the now extinct trilobite, Dalmanitina socialis, may enable them to be sensitive to the light-field information and simultaneously perceive both close and distant objects in the environment. Here, inspired by the optical structure of their eyes, we demonstrate a nanophotonic light-field camera incorporating a spin-multiplexed bifocal metalens array capable of capturing high-resolution light-field images over a record depth-of-field ranging from centimeter to kilometer scale, simultaneously enabling macro and telephoto modes in a snapshot imaging. By leveraging a multi-scale convolutional neural network-based reconstruction algorithm, optical aberrations induced by the metalens are eliminated, thereby significantly relaxing the design and performance limitations on metasurface optics.