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While deep neural networks have revolutionized image denoising capabilities, their deployment on edge devices remains challenging due to substantial computational and memory requirements. To this end, we present DnLUT, an ultra-efficient…
Lithium niobate (LN) metasurfaces exhibit remarkable Pockels effect-driven electro-optic tunability, enabling dynamic control of optical responses through external electric fields. When combined with their high second-order nonlinear…
Plasmonic metasurfaces are promising as enablers of nanoscale nonlinear optics and flat nonlinear optical components. Nonlinear optical responses of such metasurfaces are determined by the nonlinear optical properties of individual…
Flexible control light field across multiple parameters is the cornerstone of versatile and miniaturized optical devices. Metasurfaces, comprising subwavelength scatterers, offer a potent platform for executing such precise manipulations.…
Nonlinear metasurface holography shows the great potential of metasurfaces to control the phase, amplitude, and polarization of light while simultaneously converting the frequency of the light. The possibility of tailoring the scattering…
True-time-delay (TTD) beamformers can produce wideband, squint-free beams in both analog and digital signal domains, unlike frequency-dependent FFT beams. Our previous work showed that TTD beamformers can be efficiently realized using the…
Neural networks in general, from MLPs and CNNs to attention-based Transformers, are constructed from layers of linear combinations followed by nonlinear operations such as ReLU, Sigmoid, or Softmax. Despite their strength, these…
Thermo-optical nonlinearities (TONL) in metasurfaces enable dynamic control of optical properties like transmission, reflection, and absorption through external stimuli such as laser irradiation or temperature. As slow thermal dynamics of…
Recent advances in nonlocal metasurfaces have enabled unprecedented success in shaping the wavefront of light with spectral selectivity, offering new solutions for many emerging nanophotonics applications. The ability to tune both the…
Molding the flow of light at the nanoscale has been a grand challenge of nanophotonics for decades. It is now widely recognized that metasurfaces represent a chip-scale nanophotonics array technology capable of comprehensively controlling…
The rapid scaling of deep neural networks comes at the cost of unsustainable power consumption. While optical neural networks offer an alternative, their capabilities remain constrained by the lack of efficient optical nonlinearities. To…
Compared to the conventional metasurface design, machine learning-based methods have recently created an inspiring platform for an inverse realization of the metasurfaces. Here, we have used the Deep Neural Network (DNN) for the generation…
Efficient deployment of Deep Neural Networks (DNNs), such as Large Language Models (LLMs), on tensor accelerators is essential for maximizing computational efficiency in modern AI systems. However, achieving this is challenging due to the…
Unmanned Aerial Vehicles are reshaping Non-Terrestrial Networks by acting as agile, intelligent nodes capable of advanced analytics and instantaneous situational awareness. This article introduces a budget-friendly quadcopter platform that…
Advanced manufacturing with new bio-derived materials can be achieved faster and more economically with first-principle-based artificial intelligence and machine learning (AI/ML)-derived models and process optimization. Not only is this…
The nonlinear optical response of materials to exciting light is enhanced by resonances between the incident laser frequencies and the energy levels of the excited material. Traditionally, in molecular nonlinear spectroscopy one tunes the…
High-quality flat optical elements require efficient light deflection to large angles and over a wide wavelength spectrum. Although phase gradient metasurfaces achieve this by continuously adding phase shifts in the range of 0 to 2{\pi} to…
We introduce a novel technique for designing color filter metasurfaces using a data-driven approach based on deep learning. Our innovative approach employs inverse design principles to identify highly efficient designs that outperform all…
Nonlinear metamaterials with tailored mechanical properties have applications in engineering, medicine, robotics, and beyond. While modeling their macromechanical behavior is challenging in itself, finding structure parameters that lead to…
Nanophotonic devices excel at confining light into intense hot spots of the electromagnetic near fields, creating unprecedented opportunities for light-matter coupling and surface-enhanced sensing. Recently, all-dielectric metasurfaces with…