Multifunctional Meta-Optic Systems: Inversely Designed with Artificial Intelligence
Flat optics foresees a new era of ultra-compact optical devices, where metasurfaces serve as the foundation. Conventional designs of metasurfaces start with a certain structure as the prototype, followed by an extensive parametric sweep to accommodate the requirements of phase and amplitude of the emerging light. Regardless of how computation-consuming the process is, a predefined structure can hardly realize the independent control over the polarization, frequency, and spatial channels, which hinders the potential of metasurfaces to be multifunctional. Besides, achieving complicated and multiple functions calls for designing a meta-optic system with multiple cascading layers of metasurfaces, which introduces super exponential complexity. In this work we present an artificial intelligence framework for designing multilayer meta-optic systems with multifunctional capabilities. We demonstrate examples of a polarization-multiplexed dual-functional beam generator, a second order differentiator for all-optical computation, and a space-polarization-wavelength multiplexed hologram. These examples are barely achievable by single-layer metasurfaces and unattainable by traditional design processes.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Multifunctional Metasurface Design with a Generative Adversarial Network
Metasurfaces have enabled precise electromagnetic wave manipulation with strong potential to obtain unprecedented functionalities and multifunctional behavior in flat optical devices. These advantages in precision and fu…
Generative Adversarial NetworkComputational metaoptics for imaging
Metasurfaces -- ultrathin structures composed of subwavelength optical elements -- have revolutionized light manipulation by enabling precise control over electromagnetic waves' amplitude, phase, polarization, and spectr…
Meta-training of diffractive meta-neural networks for super-resolution direction of arrival estimation
Diffractive neural networks leverage the high-dimensional characteristics of electromagnetic (EM) fields for high-throughput computing. However, the existing architectures face challenges in integrating large-scale multi…
Direction of Arrival EstimationMulti-Task LearningReal-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders
Hyperspectral imaging has attracted significant attention to identify spectral signatures for image classification and automated pattern recognition in computer vision. State-of-the-art implementations of snapshot hypers…
image-classificationImage ClassificationSemantic SegmentationSpectral ReconstructionMetasurface-Enabled Multifunctional Single-Frequency Sensors without External Power
IoT sensors are crucial for visualizing multidimensional and multimodal information and enabling future IT applications/services such as cyber-physical space, digital twins, autonomous driving, smart cities, and virtual/…
Autonomous Driving