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As an optical processor, a Diffractive Deep Neural Network (D2NN) utilizes engineered diffractive surfaces designed through machine learning to perform all-optical information processing, completing its tasks at the speed of light…

Optics · Physics 2024-01-22 Xilin Yang , Md Sadman Sakib Rahman , Bijie Bai , Jingxi Li , Aydogan Ozcan

In this letter, we report on an analytical technique for optical investigations of semitransparent samples. By Fourier transforming optical spectra with Fabry-Perot resonances we extract information about sample thickness and its discrete…

Pixel size in cameras and other refractive imaging devices is typically limited by the free-space diffraction. However, a vast majority of semiconductor-based detectors are based on materials with substantially high refractive index. We…

Optics · Physics 2018-03-28 Bo Fan , Sandeep Inampudi , Viktor A. Podolskiy

We introduce optical polarization-insensitive high pass filters based on total internal reflection of light at the interface of two dielectric media (1D) and Bragg reflection of a multilayer stack (2D) in transmission mode. The wavevectors…

Optics · Physics 2019-11-26 Ali Pour Mohammad Qoli Vafa , Parisa Karimi , Amin Khavasi

Diffractive optical elements that divide an input beam into a set of replicas are used in many optical applications ranging from image processing to communications. Their design requires time-consuming optimization processes, which, for a…

Reconstruction of in-line holograms of unknown objects in general suffers from twin-image artifacts due to the appearance of an out-of-focus image overlapping with the desired image to be reconstructed. Computer-based iterative phase…

Optics · Physics 2021-10-28 Md Sadman Sakib Rahman , Aydogan Ozcan

We present a hybrid image classifier by mode-selective image upconversion, single pixel photodetection, and deep learning, aiming at fast processing a large number of pixels. It utilizes partial Fourier transform to extract the signature…

Optics · Physics 2021-04-21 Santosh Kumar , Ting Bu , He Zhang , Irwin Huang , Yuping Huang

We design, fabricate, and characterize multifunctional and compact diffractive microlenses with sub-wavelength thickness and the capability to simultaneously focus visible and near-infrared spectral bands at two different focal positions…

Optics · Physics 2020-04-22 Wesley A. Britton , Yuyao Chen , Fabrizio Sgrignuoli , Luca Dal Negro

Photonic computing, with potentials of high parallelism, low latency and high energy efficiency, have gained progressive interest at the forefront of neural network (NN) accelerators. However, most existing photonic computing accelerators…

Optics · Physics 2024-04-16 Ziyu Zhan , Hao Wang , Qiang Liu , Xing Fu

Recent research efforts in optical computing have gravitated towards developing optical neural networks that aim to benefit from the processing speed and parallelism of optics/photonics in machine learning applications. Among these…

Optics · Physics 2020-12-25 Deniz Mengu , Yair Rivenson , Aydogan Ozcan

In this paper, we realize the concept of analog computing using an array of engineered gradient dielectric meta-reflect-array. The proposed configuration consists of individual subwavelength silicon nanobricks in combination with fused…

Single-shot coherent diffractive imaging (CDI) using intense XUV and soft X-ray pulses holds the promise to deliver information on the three dimensional shape as well as the optical properties of nano-scale objects in a single diffraction…

Optics · Physics 2025-11-25 Paul Tuemmler , Julia Apportin , Thomas Fennel , Christian Peltz

Within the expansive domain of optical sciences, achieving the precise characterization of light beams stands as a fundamental pursuit, pivotal for various applications, including telecommunications and imaging technologies. This study…

On-chip photonic processors for neural networks have potential benefits in both speed and energy efficiency but have not yet reached the scale at which they can outperform electronic processors. The dominant paradigm for designing on-chip…

Efficient machine learning inference is essential for the rapid adoption of artificial intelligence across various domains.On-chip optical computing has emerged as a transformative solution for accelerating machine learning tasks, owing to…

Traditional glass-based optics are typically optimized for narrow spectral bands, such as the visible (400-700nm) or shortwave infrared (1000-1800nm). While the emergence of VIS-SWIR sensors (400-1700nm) offers transformative potential,…

Image and Video Processing · Electrical Eng. & Systems 2026-05-04 Vishwanath Saragadam , Niki Nezakati , Amit Roy-Chowdhury , Vivek Boominathan

Fourier phase retrieval is essential for high-definition imaging of nanoscale structures across diverse fields, notably coherent diffraction imaging. This study presents the Single impliCit neurAl Network (SCAN), a tool built upon…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Tingyou Li , Zixin Xu , Yong S. Chu , Xiaojing Huang , Jizhou Li

Under spatially-coherent light, a diffractive optical network composed of structured surfaces can be designed to perform any arbitrary complex-valued linear transformation between its input and output fields-of-view (FOVs) if the total…

Optics · Physics 2023-08-17 Md Sadman Sakib Rahman , Xilin Yang , Jingxi Li , Bijie Bai , Aydogan Ozcan

The 4f lens system is a standard Fourier-optics building block for angular control in optical platforms such as spatial light modulators, imaging systems, and data storage devices. This work presents the first nanoscale implementation of an…

Optics · Physics 2025-09-09 Mahmoud A. A. Abouelatta , Karim Achouri

Fourier single-pixel imaging (FSI) has proven capable of reconstructing high-quality two-dimensional and three-dimensional images. The utilization of the sparsity of natural images in Fourier domain allows high-resolution images to be…

Computer Vision and Pattern Recognition · Computer Science 2016-12-12 Zibang Zhang , Xueying Wang , Jingang Zhong
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