使用深度学习以张量流/角点和约5600 Lumerical模拟作为训练数据来优化单元素超表面参数。 在垂直入射光下进行的模拟。 定义超表面的特征是1.长度(L)2.宽度(W)3.高度(H)4.x方向周期性(Ux)5. y方向周期性(Uy)。 输出是周围和整个可见光的相位光谱,增量为5 nm(450 nm-800 nm)。
Additionally, the metasurface has a narrow-band high absorptivity of 0.88 at the near-infrared wavelength (1.54 μm) for laser guidance. For the optimized structure, we also analyze the potential physical mechanisms. The structure we optimized is geometrically simple, which may find practical ...
In order to accelerate the design process of electromagnetically induced transparency (EIT) metasurface, a deep learning-based EIT metasurface design method is proposed, where the spectral profile of EIT metasurface can be predicted by the forward prediction process, and the EIT metasurface geometry par...
A“super-mirror” having ultrahigh infrared reflectance is achieved by an optimized photonic contrast grating metasurface. Finding ways to achieve this exceptional performance can be enabled by implementing global optimization and machine learning elements, such as Bayesian optimization and genetic algorithm....
(that is, self-adaptive) cloak driven by deep learning and present a metasurface cloak as an example implementation. In the experiment, the metasurface cloak exhibits a millisecond response time to an ever-changing incident wave and the surrounding environment, without any human intervention. Our ...
demonstrated for the first time the possibility of performing inverse design of nanophotonic structures using an unsupervised learning system. More specifically, they used a generative adversarial network (GAN) [75] to design arbitrary geometries of metasurfaces. GANs are rather a recently developed ...
optimization.surrogatefasterSurrogate models for partial-differential equations are widely used in the design of meta-materials to rapidly evaluate the behavior of composable components. However, the training cost of accurate surrogates by machine learning can rapidly increase with the number of variables....
The metasurface can then construct complex spatial and temporal electromagnetic beams. Given the main parameters of the beam, the optimal codes can be computed by nonlinear optimization algorithms, such as genetic algorithm, particle swarm optimization, etc. The high computational complexity of these ...
splitter -- an array of gap-plasmon based nanostructure which on illumination with a light beam shows PSHE due to rapid gradient of phase on the metasurface. The optimization is done in near infrared region(NIR) and extended to optical for high power efficiency in the reflected LCP and RCP ...
The introduction of DL into the inverse-design process makes this problem tractable, enabling optimization runtimes to be measurable in days rather than months and allowing designers to establish exhaustive metasurface robustness guarantees.Keywords: deep learning; fabrication; robustness; supercell; ...