Varifocal Metalenses: Harnessing Polarization-Dependent Superposition for Continuous Focal Length Control.

Traditional varifocal lenses are bulky and mechanically complex. Emerging active metalenses promise compactness and design flexibility but face issues like mechanical tuning reliability and nonlinear focal length tuning due to additional medium requirements. In this work, we propose a varifocal metalens design based on superimposing light intensity distributions from two orthogonal polarization states. This approach enables continuous and precise focal length control within the visible spectrum, while maintaining relatively high focusing efficiencies (∼41% in simulation and ∼28% in measurement) and quality. In experimental validation, the metalens exhibited flexible tunability, with the focal length continuously adjustable between two spatial positions upon variation of the incident polarization angle. The MTF results showed high contrast reproduction and sharp imaging, with a Strehl ratio of >0.7 for all polarization angles. With compactness, design flexibility, and high focusing quality, the proposed varifocal metalens holds potential for diverse applications, advancing adaptive and versatile optical devices.

Metasurface-empowered snapshot hyperspectral imaging with convex/deep (CODE) small-data learning theory.

Hyperspectral imaging is vital for material identification but traditional systems are bulky, hindering the development of compact systems. While previous metasurfaces address volume issues, the requirements of complicated fabrication processes and significant footprint still limit their applications. This work reports a compact snapshot hyperspectral imager by incorporating the meta-optics with a small-data convex/deep (CODE) deep learning theory. Our snapshot hyperspectral imager comprises only one single multi-wavelength metasurface chip working in the visible window (500-650 nm), significantly reducing the device area. To demonstrate the high performance of our hyperspectral imager, a 4-band multispectral imaging dataset is used as the input. Through the CODE-driven imaging system, it efficiently generates an 18-band hyperspectral data cube with high fidelity using only 18 training data points. We expect the elegant integration of multi-resonant metasurfaces with small-data learning theory will enable low-profile advanced instruments for fundamental science studies and real-world applications.

Topological Encoded Vector Beams for Monitoring Amyloid-Lipid Interactions in Microcavity.

Lasers are the pillars of modern photonics and sensing. Recent advances in microlasers have demonstrated its extraordinary lasing characteristics suitable for biosensing. However, most lasers utilized lasing spectrum as a detection signal, which can hardly detect or characterize nanoscale structural changes in microcavity. Here the concept of amplified structured light-molecule interactions is introduced to monitor tiny bio-structural changes in a microcavity. Biomimetic liquid crystal droplets with self-assembled lipid monolayers are sandwiched in a Fabry-Pérot cavity, where subtle protein-lipid membrane interactions trigger the topological transformation of output vector beams. By exploiting Amyloid ß (Aß)-lipid membrane interactions as a proof-of-concept, it is demonstrated that vector laser beams can be viewed as a topology of complex laser modes and polarization states. The concept of topological-encoded laser barcodes is therefore developed to reveal dynamic changes of laser modes and Aß-lipid interactions with different Aß assembly structures. The findings demonstrate that the topology of vector beams represents significant features of intracavity nano-structural dynamics resulted from structured light-molecule interactions.