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Related papers: Large-Area Fabrication-Aware Computational Diffrac…

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We report a monochrome multi-task diffractive network architecture that leverages illumination phase multiplexing to dynamically reconfigure its output function and accurately implement a large group of complex-valued linear transformations…

Optics · Physics 2025-12-09 Xiao Wang , Aydogan Ozcan

Designing free-form photonic devices is fundamentally challenging due to the vast number of possible geometries and the complex requirements of fabrication constraints. Traditional inverse-design approaches--whether driven by human…

Optics · Physics 2025-04-25 Dongjin Seo , Soobin Um , Sangbin Lee , Jong Chul Ye , Haejun Chung

Imaging techniques such as functional near-infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT) achieve deep, non-invasive sensing in turbid media, but they are constrained by the photon budget. Wavefront shaping (WFS) can…

Optics · Physics 2026-04-21 Pablo Jara , Arthur Goetschy , Hui Cao , Alexey Yamilov

In optical devices like diffraction gratings and Fresnel lenses, light wavefront is engineered through the structuring of device surface morphology, within thicknesses comparable to the light wavelength. Fabrication of such diffractive…

Optics · Physics 2021-07-28 S. L. Oscurato , F. Reda , M. Salvatore , F. Borbone , P. Maddalena , A. Ambrosio

Hybrid optical systems combining refractive and diffractive optical responses have the potential to support new types of optical behavior, but they are difficult to model and optimize due to the disparate spatial scales and physics…

Optical neural networks (ONNs) are emerging as a promising neuromorphic computing paradigm for object recognition, offering unprecedented advantages in light-speed computation, ultra-low power consumption, and inherent parallelism. However,…

As the realm of spectral imaging applications extends its reach into the domains of mobile technology and augmented reality, the demands for compact yet high-fidelity systems become increasingly pronounced. Conventional methodologies,…

Diffractive deep neural networks (D2NNs), which perform computation using light instead of electrons, offer a promising pathway toward accelerating artificial intelligence by leveraging the inherent advantages of optics in speed,…

Optics · Physics 2025-07-24 Haoyu Wang , Yanmin Zhu , Tong Fu

Multilevel diffractive lenses (MDLs) have emerged as an alternative to both conventional diffractive optical elements (DOEs) and metalenses for applications ranging from imaging to holographic and immersive displays. Recent work has shown…

Multispectral imaging has been used for numerous applications in e.g., environmental monitoring, aerospace, defense, and biomedicine. Here, we present a diffractive optical network-based multispectral imaging system trained using deep…

Optics · Physics 2023-04-07 Deniz Mengu , Anika Tabassum , Mona Jarrahi , Aydogan Ozcan

Deep optical optimization has recently emerged as a new paradigm for designing computational imaging systems using only the output image as the objective. However, it has been limited to either simple optical systems consisting of a single…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Xinge Yang , Qiang Fu , Wolfgang Heidrich

This work presents the design and fabrication of simple, polymeric, structure-based optical filters that simultaneously focus light. These filters represent a novel design at the boundary between diffractive optics and metasurfaces that may…

Optics · Physics 2020-09-22 Mansoor A. Sultan , Fatih Balli , Daniel L. Lau , J. T. Hastings

As a representative next-generation device/circuit technology beyond CMOS, diffractive optical neural networks (DONNs) have shown promising advantages over conventional deep neural networks due to extreme fast computation speed (light…

Machine Learning · Computer Science 2023-04-05 Shanglin Zhou , Yingjie Li , Minhan Lou , Weilu Gao , Zhijie Shi , Cunxi Yu , Caiwen Ding

Synthesizing realistic microstructure images conditioned on processing parameters is crucial for understanding process-structure relationships in materials design. However, this task remains challenging due to limited training micrographs…

Materials Science · Physics 2025-11-21 Hoang Cuong Phan , Minh Tien Tran , Chihun Lee , Hoheok Kim , Sehyeok Oh , Dong-Kyu Kim , Ho Won Lee

Microscopes face a trade-off between spatial resolution, field-of-view, and frame rate -- improving one of these properties typically requires sacrificing the others, due to the limited spatiotemporal throughput of the sensor. To overcome…

3D engineering of matter has opened up new avenues for designing systems that can perform various computational tasks through light-matter interaction. Here, we demonstrate the design of optical networks in the form of multiple diffractive…

Computer Vision and Pattern Recognition · Computer Science 2021-03-29 Jingxi Li , Deniz Mengu , Nezih T. Yardimci , Yi Luo , Xurong Li , Muhammed Veli , Yair Rivenson , Mona Jarrahi , Aydogan Ozcan

Diffractive deep neural networks (D2NNs) are composed of successive transmissive layers optimized using supervised deep learning to all-optically implement various computational tasks between an input and output field-of-view (FOV). Here,…

Diffractive lenses have recently been applied to the domain of multispectral imaging in the X-ray and UV regimes where they can achieve very high resolution as compared to reflective and refractive optics. Conventionally, spectral…

Image and Video Processing · Electrical Eng. & Systems 2020-05-26 Evan Widloski , Ulas Kamaci , Farzad Kamalabadi

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.…

Deep neural networks (DNNs) have substantial computational requirements, which greatly limit their performance in resource-constrained environments. Recently, there are increasing efforts on optical neural networks and optical computing…

Machine Learning · Computer Science 2021-04-05 Yingjie Li , Ruiyang Chen , Berardi Sensale Rodriguez , Weilu Gao , Cunxi Yu
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