With the exponential growth in demand for high-speed data transmission, the 5G system infrastructure, despite its impressive peak data rate of 10 gigabits per second, is increasingly inadequate for ...

The proposed diffractive deep neural network employs orbital angular momentum encoding and diffractive layers to process spatial information from handwritten digits, offering a robust and versatile ...

To address this issue, Scientist in China showcases the use of deep diffractive neural networks (D2NNs) to construct a series of high-dimensional quantum gates, which are encoded by the spatial modes ...

State-of-the-art neural networks depend on linear operations, such as matrix-vector multiplications and convolutions. While dedicated processors like GPUs and TPUs exist for these operations, they ...

Layered metasurfaces trained as optical neural networks enable multifunctional holograms and security features, integrating neural computation principles with nanostructured optics to create a ...

The advent of deep neural networks (DNNs) has ushered in a paradigm shift, enabling the development of non-iterative, feed-forward digital image denoising approaches. These DNN-based methods exhibit ...

They revealed that simpler-to-implement phase encoding matches the accuracy of data repetition strategies across various test datasets. While data repetition-based diffractive blocks cannot provide ...