相关论文: Inverse-designed Silicon Carbide Quantum and Nonli…
Attribute to their robustness against loss and external noise, nonreciprocal photonic devices hold great promise for applications in quantum information processing. Recent advancements have demonstrated that nonreciprocal optical…
Thin-film cavities containing layers of M\"ossbauer nuclei have been demonstrated to be a rich platform for x-ray quantum optics. At low excitation, these systems can be described by effective few-level schemes, thereby providing tunable…
Nonreciprocal devices - in which light is transmitted with different efficiencies along opposite directions - are key technologies for modern photonic applications, yet their compact and miniaturized implementation remains an open…
Here, we present a new approach based on manifold learning for knowledge discovery and inverse design with minimal complexity in photonic nanostructures. Our approach builds on studying sub-manifolds of responses of a class of…
We present an accurate differentiable parametrization scheme for topological optimization and inverse design of passive components of integrated Si photonics. We show that the most of operations in the transformation chain from control…
Nanophotonic device design aims to optimize photonic structures to meet specific requirements across various applications. Inverse design has unlocked non-intuitive, high-dimensional design spaces, enabling the discovery of high-performance…
We introduce a new type of lens that focuses a plane wave into a spherical one, where light comes from all directions. Our method also suggests the design of ideal optical tweezers or, in the reverse direction, photo-detection of nearly all…
A set of grating couplers that convert plane waves into odd pairs of plasmons supported by extremely thin layers of doped indium tin oxide is designed. The inverse design approach is implemented to improve the efficiency of ordinary…
Magnonic logic gates represent a crucial step toward realizing fully magnonic data processing systems without reliance on conventional electronic or photonic elements. Recently, a universal and reconfigurable inverse-design device has been…
Narrowband perfect absorbers are interesting for spectrum sensing, molecular detection, and infrared imaging. However, their design remains constrained by intuitive, iterative methods that lack flexibility, while also facing challenges in…
Designing complex physical systems, including photonic structures, is typically a tedious trial-and-error process that requires extensive simulations with iterative sweeps in multi-dimensional parameter space. To circumvent this…
Controlling the flow of broadband electromagnetic energy at the nanoscale remains a critical challenge in optoelectronics. Surface plasmon polaritons (or plasmons) provide subwavelength localization of light, but are affected by significant…
Topology optimization methods for inverse design of nano-photonic systems have recently become extremely popular and are presented in various forms and under various names. Approaches comprise gradient and non-gradient based algorithms…
Silicon photonics lacks a second-order nonlinear optical response in general because the typical constituent materials are centro-symmetric and lack inversion symmetry, which prohibits second-order nonlinear processes such as second…
Photonic inverse design and, especially, topology optimization, enable dielectric cavities with deeply sub-diffraction mode volumes and high quality factors, thus offering a powerful platform for enhanced light-matter coupling. Here, we…
Inverse design of RF passive components from S-parameters is a high-dimensional, ill-posed problem, and prior generative approaches are limited to single-layer binary-metallization structures. This paper presents an inverse design approach…
We propose an efficient inverse design approach for multifunctional optical elements based on adaptive deep diffractive neural networks (a-D$^2$NNs). Specifically, we introduce a-D$^2$NNs and design two-layer diffractive devices that can…
Silicon carbide is among the leading quantum information material platforms due to the long spin coherence and single-photon emitting properties of its color center defects. Applications of silicon carbide in quantum networking, computing,…
Quantum photonic technologies rely on the ability to generate, manipulate, and interfere indistinguishable single photons on a scalable platform. Among the various approaches, spontaneous parametric down-conversion (SPDC) remains one of the…
On-chip optical neural networks (ONNs) have recently emerged as an attractive hardware accelerator for deep learning applications, characterized by high computing density, low latency, and compact size. As these networks rely heavily on…