Search

Imaging polarimetry based on dielectric metasurface is well-known for its ultra-compactness and high integration. However, previous works suffer from low energy efficiency, limited restrictions on choice of target polarization states, or inability to focus light. Here, by inverse design, we numerically demonstrate a multi-foci metalens-based polarimetry that can simultaneously separate and focus the four free-chosen elliptical polarization states at the wavelength of 10.6 \mu m. Such a full-stokes polarimetry features an average absolute efficiency up to 54.63%, and an average relative error as low as 0.00137%. This spatial-multiplexing-free full stokes polarimetry exceeds the theoretical maximum efficiency of traditional polarization-filtering counterparts, and resolves the restriction faced by the orthogonal polarization-multiplexed method.

Despite excellent performance in image generation, Generative Adversarial Networks (GANs) are notorious for its requirements of enormous storage and intensive computation. As an awesome ''performance maker'', knowledge distillation is demonstrated to be particularly efficacious in exploring low-priced GANs. In this paper, we investigate the irreplaceability of teacher discriminator and present an inventive discriminator-cooperated distillation, abbreviated as DCD, towards refining better feature maps from the generator. In contrast to conventional pixel-to-pixel match methods in feature map distillation, our DCD utilizes teacher discriminator as a transformation to drive intermediate results of the student generator to be perceptually close to corresponding outputs of the teacher generator. Furthermore, in order to mitigate mode collapse in GAN compression, we construct a collaborative adversarial training paradigm where the teacher discriminator is from scratch established to co-train with student generator in company with our DCD. Our DCD shows superior results compared with existing GAN compression methods. For instance, after reducing over 40x MACs and 80x parameters of CycleGAN, we well decrease FID metric from 61.53 to 48.24 while the current SoTA method merely has 51.92. This work's source code has been made accessible at https://github.com/poopit/DCD-official.

This paper proposes a content relationship distillation (CRD) to tackle the over-parameterized generative adversarial networks (GANs) for the serviceability in cutting-edge devices. In contrast to traditional instance-level distillation, we design a novel GAN compression oriented knowledge by slicing the contents of teacher outputs into multiple fine-grained granularities, such as row/column strips (global information) and image patches (local information), modeling the relationships among them, such as pairwise distance and triplet-wise angle, and encouraging the student to capture these relationships within its output contents. Built upon our proposed content-level distillation, we also deploy an online teacher discriminator, which keeps updating when co-trained with the teacher generator and keeps freezing when co-trained with the student generator for better adversarial training. We perform extensive experiments on three benchmark datasets, the results of which show that our CRD reaches the most complexity reduction on GANs while obtaining the best performance in comparison with existing methods. For example, we reduce MACs of CycleGAN by around 40x and parameters by over 80x, meanwhile, 46.61 FIDs are obtained compared with these of 51.92 for the current state-of-the-art. Code of this project is available at https://github.com/TheKernelZ/CRD.

Metalenses, featuring ultra-compactness and CMOS compatibility, are limited by the compromise between the diameter, numerical aperture, and working waveband. To address this problem, we propose and numerically demonstrate a centimeter-scale metasurface-refractive hybrid metalens working in the band of 440 - 700 nm. Revisiting the general Snell law, we present the phase profile of a chromatic aberration correction metasurface that can apply to a plano-convex refractive lens of an arbitrary surface type. Simulated by our semi-vector method, the designed achromatic hybrid metalens achieves 81% chromatic aberration suppression and polarization insensitivity. Broadband imaging results of the hybrid metalens are further provided, verifying the achromatism of the designed hybrid metalens. It can find applications in camera lenses and other optical systems that need compact, high-performance lenses., Comment: 10 pages, 5 figures

Zoom metalens doublet exhibits unprecedented advantages over the traditional zoom lens in many aspects, like ultra-compactness, CMOS compatibility, and miniaturization. However, most of them can only work in a narrow band due to chromatic aberration. Here, we numerically demonstrate a broadband achromatic zoom metalens doublet inspired by the Moir\'e lens principle. This design is achieved by globally optimizing the multi-wavelength phase profiles of the metalens doublet in the visible. The doublet can achieve achromatic continuous 1-10 zoom range at wavelengths of 440 nm, 540 nm, and 640 nm, featuring high focusing efficiency up to 86.5% and polarization insensitivity., Comment: 4 pages, 5 figures

Multiplexed planar printings, made of single or few layer micro and nano optical platforms, are essential for high capacity display, information storage and encryption. Although having been developed rapidly, the demonstrated channels are still limited and also lack instantaneity. Here, holograms and printings, always regarded as two independent information coding domains with totally different principles, are combined together through our proposed angle multiplexing framework, leading to multiplexed printings with hundreds of channels. Based on such approach, we experimentally encode respectively 25 gray scale printings into 25 angles and even 8 gray scale videos into 8 angles with a phase-only spatial light modulator. As a bridge between printings and holograms, our method allows to generate printings combining various holographic methods. Beneficial from this, we demonstrate a gradient metasurface based 324 channel printing which multiplexes angles, polarizations and wavelengths simultaneously. Our work paves the way to flexibly angle-dependent printing display and massively multiplexed encryption systems., Comment: 16 pages, 5 figures

The scalability of optical addressing is one of the key challenges for the large-scale trapped-ion quantum computing (QC). Metasurfaces is a promising solution due to excellent optical performance, integration, and miniaturization. Here, we propose and numerically demonstrate a design of integrated scalable metalens array (ISMA) working in the UV 350nm range for optical addressing. These ISMAs can focus the collimated individual addressing beams array into diffraction-limited spots array, featuring crosstalk below 0.82%, focusing efficiency as high as 36.90%. For various applications, the x-polarized, polarization-insensitive and right-handed circularly polarized ISMA are designed. The design proposed in this paper can also find applications in optical trapping., Comment: 7 pages,3 figures

Metasurface-based lenses (metalenses) offer specific conceptual advantages compared to ordinary refractive lenses. For example, it is possible to tune the focal length of a metalens doublet by varying the relative angle between the two metalenses while fixing their distance, leading to an extremely compact zoom lens. An improved polarization-insensitive design based on silicon-nanocylinders on silica substrates is presented. This design is realized and characterized experimentally at 1550 nm wavelength. By varying the relative angle between the metalenses in steps of 10 degrees, tuning of the doublet focal length is demonstrated from -54 mm to -+3 mm to +54 mm. This results in a zoom factor of an imaging system varying between 1 and 18. For positive focal lengths, the doublet focusing efficiency has a minimum of 34% and a maximum of 83%. Experiment and theory are in very good agreement.