![]() Nonlocal scatterer for compact wave-based analog computing. Compact incoherent image differentiation with nanophotonic structures. Parallel convolutional processing using an integrated photonic tensor core. All-optical machine learning using diffractive deep neural networks. Deep learning with coherent nanophotonic circuits. Photonics for artificial intelligence and neuromorphic computing. An optical neural network using less than 1 photon per multiplication. Reconfigurable nonlinear optical element using tunable couplers and inverse-designed structure. A scheme for efficient quantum computation with linear optics. Adapting Mach–Zehnder mesh equalizers in direct-detection mode-division-multiplexed links. Design of compact meta-crystal slab for general optical convolution. Analog computing using reflective plasmonic metasurfaces. Plasmonic computing of spatial differentiation. Laplace metasurfaces for optical analog computing based on quasi-bound states in the continuum. Ultracompact meta-imagers for arbitrary all-optical convolution. A single inverse-designed photonic structure that performs parallel computing. An optical neural chip for implementing complex-valued neural network. Inverse-designed metastructures that solve equations. Performing mathematical operations with metamaterials. Inverse-designed metastructures together with reconfigurable couplers to compute forward scattering. Solving integral equations in free-space with inverse-designed ultrathin optical metagratings. These examples demonstrate that these techniques have the potential to enable larger-scale wave-based analogue computing platforms.Ĭordaro, A. We also designed a 10 × 10 matrix using the proposed 2D computational method. We designed and experimentally demonstrated a vector–matrix product for a 2 × 2 matrix and a 3 × 3 matrix. This results in compact amorphous lens systems that are generally feed-forward and low-resonance. ![]() Here we employ a two-dimensional (2D) inverse-design method based on the effective index approximation with a low-index contrast constraint. This results in structures that are narrow-bandwidth and highly sensitive to fabrication errors. Furthermore, a typical inverse-design procedure is limited to a small computational domain and therefore tends to employ resonant features to achieve its objectives. However, due to computational difficulties, scaling up these metastructures to handle a large number of data channels is not trivial. Inverse-designed silicon photonic metastructures offer an efficient platform to perform analogue computations with electromagnetic waves.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |