High speed optical imaging is a critical tool for the observation of transient, nonrepeatable phenomena. In this talk, we discuss our recent progress on a spatiotemporally encoded ultrafast imaging system. Our approach involves recording of ultrafast events encoded using nano – scribed spatiotemporal masks on a slow camera. The captured data is then reconstructed into a sequence of ultrafast frames via a U – net based deep learning model. We will present both simulation and experimental results.
Traditional cameras are limited to capturing only the intensity distribution of light, lacking other important information. We present a novel approach to overcome this limitation by incorporating metasurfaces - thin layers of nanostructures - into standard cameras. These metasurfaces can encode light information of different dimensions, including polarization, frequency, and time, through the unique optical responses of their constituent meta-atoms. As a result, a single snapshot of the light field can capture all its properties. We also use deep-learning-based recovery algorithms that enable real-time retrieval of multi-dimensional images. This breakthrough has enormous potential to revolutionize the way we collect and analyze light information, leading to new applications and insights in various fields.
We present a compact, spatiotemporally encoded, deep learning-enabled, single-shot ultrafast imaging system. We simulate the forward light-transport process of an ultrafast event encoded by a random spatiotemporal encoding mask and construct a U-net-based deep learning model to reconstruct the ultrafast event sequences. Trained on simulated ultrafast events consisting of various geometric shapes and handwritten digits with random locations and speeds, the deep learning model can reconstruct multi-frame ultrafast event sequences from simulated single-shot measurements by a normal camera with high reconstruction accuracy and noise tolerance. We also present preliminary fabrication results of spatiotemporal masks. This work provides a simple, cost-effective, single-shot method for studying nonrepetitive ultrafast transient processes.
Transverse spin angular momentum (t-SAM) is a spin with a vector perpendicular to the light propagation direction, naturally appearing in tightly confined electromagnetic waves. For the first time, we successfully generated t-SAM in a spatial point of maximum intensity of focused light using an asymmetric metasurface. The designed metasurface provides complete phase and polarization control and allows for the manipulation of both electric and magnetic transverse spin distribution. The results were obtained through both theoretical and experimental methods, demonstrating the metasurface's ability to generate a strong transverse spin in a focal point ensuring non-zero net spin in the focal plane. This discovery has potential applications in optomechanics, quantum optics, nanometrology, and directional scattering.
We theoretically and experimentally demonstrate a novel design of broadband double-layer achromatic metalens working for wavelengths ranging from 400-700 nm. By exploiting a dielectric staircase layer, we significantly extended the range of attainable group delay with a library of nanoantennas with moderate shape complexity. Our experiment results show that our metalens has a Strehl ratio of >80%, and the focal length variation is less than 3% over the entire visible band, exhibiting excellent broadband achromatic focusing. Our work could shed light on overcoming the size and bandwidth limits of achromatic metalenses and facilitate applications such as microscopy and spectral imaging.
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