Deep-Learning-Assisted Simultaneous Target Sensing and Super-Resolution Imaging.

Metasurfaces have recently experienced revolutionary progress in sensing and super-resolution imaging fields, mainly due to their manipulation of electromagnetic waves on subwavelength scales. However, on the one hand, the addition of metasurfaces can multiply the complexity of retrieving target information from detected electromagnetic fields. On the other hand, many existing studies utilize deep learning methods to provide compelling tools for electromagnetic problems but mainly concentrate on resolving one single function, limiting their versatilities. In this work, a multifunctional deep learning network is demonstrated to reconstruct diverse target information in a metasurface-target interactive system. First, a preliminary experiment verifies that the metasurface-involved scenario can tolerate the system noises. Then, the captured electric field distributions are fed into the multifunctional network, which can not only accurately sense the quantity and relative permittivity of targets but also generate super-resolution images precisely. The deep learning network, thus, paves an alternative way to recover the targets' information in metasurface-target interactive systems, accelerating the progression of target sensing and superimaging areas. Besides, another new network that allows forward electromagnetic prediction is also proposed and demonstrated. To sum up, the deep learning methodology may hold promise for inverse reconstructions or forward predictions in many electromagnetic scenarios.

Spin-decoupled excitation and wavefront shaping of structured surface waves via on-chip terahertz metasurfaces.

Surface waves (SWs) are of great importance in terahertz (THz) photonics applications due to their subwavelength properties. Hence, it is crucial to develop surface wavefront shaping techniques, which is urgent in modern information technologies. In this paper, a new scheme is proposed to realize SW excitation and spin-decoupled wavefront shaping with an ultracompact planar meta-device working in the THz range. The meta-device is composed of two parts: meta-atoms (in the center) and plasmonic metals (on the left and right sides). By carefully setting the geometry size and rotation angle of each meta-atom, the encoded spin-decoupled phase distributions for both left circularly polarized (LCP) and right circularly polarized (RCP) incident THz waves are determined. In this way, circularly polarized (CP) incident THz waves can be converted to SWs propagating along plasmonic metals with unique wavefront profiles, i.e., Bessel and focusing profiles. Full-wave simulations and THz near-field scanning experiments were performed to verify the functionalities of the meta-device, both of which are in great agreement with theoretical predictions. Our findings may provide more solutions to design THz integrated photonic devices and systems.

Ultrathin All-Angle Hyperbolic Metasurface Retroreflectors Based on Directed Routing of Canalized Plasmonics.

Retroreflectors that can accurately redirect the incident waves in free space back along their original channels provide unprecedented opportunities for light manipulation. However, to the best of our knowledge, they suffer from either the bulky size, narrow angular bandwidths, or time-consuming postprocessing, which essentially limits their further applications. Here, a scheme for designing ultrathin all-angle real-time retroreflectors based on hyperbolic plasmonic metasurfaces is proposed and experimentally demonstrated. The physical mechanism underlying the scheme is the orthogonality between the traveling waves in free space and the canalized spoof surface plasmon on the hyperbolic plasmonic metasurfaces, which guarantee their high-efficiency and all-angle mutual conversion. In this case, the strong confinement characteristic that benefited from the enhanced light-matter interaction enables us to route and retroreflect the canalized spoof surface plasmon with extremely thin structures. As proof of the scheme, a retroreflector prototype with a thickness approximately equal to the central wavelength is designed and fabricated. Further experimental investigation obtains a half-power field of view up to 53° and a maximum efficiency of 83.2%. This scheme can find promising applications in target detection, remote sensing, and diverse on-chip light control devices.

Smoking, life expectancy, and chronic disease in South Korea, Singapore, and the United States: A microsimulation model.

The substantial social and economic burden attributable to smoking is well-known, with heavy smokers at higher risk of chronic disease and premature mortality than light smokers and nonsmokers. In aging societies with high rates of male smoking such as in East Asia, smoking is a leading preventable risk factor for extending lives (including work-lives) and healthy aging. However, little is known about whether smoking interventions targeted at heavy smokers relative to light smokers lead to disproportionately larger improvements in life expectancy and prevalence of chronic diseases and how the effects vary across populations. Using a microsimulation model, we examined the health effects of smoking reduction by simulating an elimination of smoking among subgroups of smokers in South Korea, Singapore, and the United States. We found that life expectancy would increase by 0.2 to 1.5 years among light smokers and 2.5 to 3.7 years among heavy smokers. Whereas both interventions led to an increased life expectancy and decreased the prevalence of chronic diseases in all three countries, the life-extension benefits were greatest for those who would otherwise have been heavy smokers. Our findings illustrate how smoking interventions may have significant economic and social benefits, especially for life extension, that vary across countries.