Metasurfaces designed by a bidirectional deep neural network and iterative algorithm for generating quantitative field distributions

Metasurfaces, which are the two-dimensional counterparts of metamaterials, have demonstrated unprecedented capabilities to manipulate the wavefront of electromagnetic waves in a single flat device. Despite various advances in this field, the unique functionalities achieved by metasurfaces have come at the cost of the structural complexity, resulting in a time-consuming parameter sweep for the conventional metasurface design. Although artificial neural networks provide a flexible platform for significantly improving the design process, the current metasurface designs are restricted to generating qualitative field distributions. In this study, we demonstrate that by combining a tandem neural network and an iterative algorithm, the previous restriction of the design of metasurfaces can be overcome with quantitative field distributions. As proof-of-principle examples, metalenses predicted via the designed network architecture that possess multiple focal points with identical/orthogonal polarisation states, as well as accurate intensity ratios (quantitative field distributions), were numerically calculated and experimentally demonstrated. The unique and robust approach for the metasurface design will enable the acceleration of the development of devices with high-accuracy functionalities, which can be applied in imaging, detecting, and sensing

Geometric Phase Generated Optical Illusion

Abstract An optical illusion, such as “Rubin’s vase”, is caused by the information gathered by the eye, which is processed in the brain to give a perception that does not tally with a physical measurement of the stimulus source. Metasurfaces are metamaterials of reduced dimensionality which have opened up new avenues for flat optics. The recent advancement in spin-controlled metasurface holograms has attracted considerate attention, providing a new method to realize optical illusions. We propose and experimentally demonstrate a metasurface device to generate an optical illusion. The metasurface device is designed to display two asymmetrically distributed off-axis images of “Rubin faces” with high fidelity, high efficiency and broadband operation that are interchangeable by controlling the helicity of the incident light. Upon the illumination of a linearly polarized light beam, the optical illusion of a ‘vase’ is perceived. Our result provides an intuitive demonstration of the figure-ground distinction that our brains make during the visual perception. The alliance between geometric metasurface and the optical illusion opens a pathway for new applications related to encryption, optical patterning, and information processing

Detection of recurrent cytogenetic aberrations in multiple myeloma: A comparison between MLPA and iFISH

Multiple myeloma (MM) is a genetically heterogeneous disease with diverse clinical characteristics and outcomes. Recently, multiplex ligation-dependent probe amplification (MLPA) has emerged as an effective and robust method for the detection of cytogenetic aberrations in MM patients. In the present study, MLPA analysis was applied to analyze cytogenetics of CD138 tumor cells of 59 MM samples, and its result was compared, retrospectively, with the interphase fluorescence in situ hybridization (iFISH) data. We firstly established the normal range of each of the 42 diagnostic probes using healthy donor samples. A total of 151 aberrations were detected in 59 patient samples, and 49/59 cases (83.1%) harbored at least one copy number variation. Overall, 0–7 aberrations were detected per case using MLPA, indicating the heterogeneity and complexity of MM cytogenetics. We showed the high efficiency of MLPA and the high congruency of the two methods to assess cytogenetic aberrations. Considering that MLPA analysis is not reliable when the aberration only exits in a small population of tumor cells, it is essential to use both MLPA and iFISH as complementary techniques for the diagnosis of MM

Two-Degree Vibration Analysis of a Horizontal Axis Turbine Blade by Finite Differential Methods

Two-degree vibration partial differential equations of large horizontal axis turbine blades were established by Kallesøe’s model and Greenberg unsteady aerodynamic theory. By means of the finite difference discretization and cantilever beam boundary condition, the equations of blades can be simplified as a general vibration system. Then a linear stationary state space on the system was built. The blade tip vibration in autonomous and nonautonomous system can be simulated by MATLAB vibration toolboxes in time domain. The convergent, flutter, and divergent vibration curves were plotted in the directions of lead-lag and flapping

Two-Degree Vibration Analysis of a Horizontal Axis Turbine Blade by Finite Differential Methods

Two-degree vibration partial differential equations of large horizontal axis turbine blades were established by Kallesøe’s model and Greenberg unsteady aerodynamic theory. By means of the finite difference discretization and cantilever beam boundary condition, the equations of blades can be simplified as a general vibration system. Then a linear stationary state space on the system was built. The blade tip vibration in autonomous and nonautonomous system can be simulated by MATLAB vibration toolboxes in time domain. The convergent, flutter, and divergent vibration curves were plotted in the directions of lead-lag and flapping