no code implementations • 16 Mar 2024 • Che-Yung Shen, Jingxi Li, Tianyi Gan, Yuhang Li, Langxing Bai, Mona Jarrahi, Aydogan Ozcan
These wavelength-multiplexed patterns are projected onto a single field-of-view (FOV) at the output plane of the diffractive processor, enabling the capture of quantitative phase distributions of input objects located at different axial planes using an intensity-only image sensor.
no code implementations • 4 Feb 2024 • Guangdong Ma, Xilin Yang, Bijie Bai, Jingxi Li, Yuhang Li, Tianyi Gan, Che-Yung Shen, Yijie Zhang, Yuzhu Li, Mona Jarrahi, Aydogan Ozcan
We demonstrated the feasibility of this reconfigurable multiplexed diffractive design by approximating 256 randomly selected permutation matrices using K=4 rotatable diffractive layers.
no code implementations • 30 Jan 2024 • Jingxi Li, Yuhang Li, Tianyi Gan, Che-Yung Shen, Mona Jarrahi, Aydogan Ozcan
Here, we present a complex field imager design that enables snapshot imaging of both the amplitude and quantitative phase information of input fields using an intensity-based sensor array without any digital processing.
no code implementations • 17 Jan 2024 • Jingtian Hu, Kun Liao, Niyazi Ulas Dinc, Carlo Gigli, Bijie Bai, Tianyi Gan, Xurong Li, Hanlong Chen, Xilin Yang, Yuhang Li, Cagatay Isil, Md Sadman Sakib Rahman, Jingxi Li, Xiaoyong Hu, Mona Jarrahi, Demetri Psaltis, Aydogan Ozcan
To resolve subwavelength features of an object, the diffractive imager uses a thin, high-index solid-immersion layer to transmit high-frequency information of the object to a spatially-optimized diffractive encoder, which converts/encodes high-frequency information of the input into low-frequency spatial modes for transmission through air.
no code implementations • 15 Jan 2024 • Bijie Bai, Ryan Lee, Yuhang Li, Tianyi Gan, Yuntian Wang, Mona Jarrahi, Aydogan Ozcan
This information hiding transformation is valid for infinitely many combinations of secret messages, all of which are transformed into ordinary-looking output patterns, achieved all-optically through passive light-matter interactions within the optical processor.
no code implementations • 8 Nov 2023 • Che-Yung Shen, Jingxi Li, Tianyi Gan, Mona Jarrahi, Aydogan Ozcan
Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with various applications ranging from imaging to beam focusing.
no code implementations • 17 Sep 2023 • Cagatay Isil, Tianyi Gan, F. Onuralp Ardic, Koray Mentesoglu, Jagrit Digani, Huseyin Karaca, Hanlong Chen, Jingxi Li, Deniz Mengu, Mona Jarrahi, Kaan Akşit, Aydogan Ozcan
Our results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of ~30-40%.
no code implementations • 29 Aug 2023 • Bijie Bai, Xilin Yang, Tianyi Gan, Jingxi Li, Deniz Mengu, Mona Jarrahi, Aydogan Ozcan
Our analyses revealed the efficacy of this P-D2NN design in unidirectional image magnification and demagnification tasks, producing high-fidelity magnified or demagnified images in only one direction, while inhibiting the image formation in the opposite direction - confirming the desired unidirectional imaging operation.
no code implementations • 20 Apr 2023 • Md Sadman Sakib Rahman, Tianyi Gan, Emir Arda Deger, Cagatay Isil, Mona Jarrahi, Aydogan Ozcan
In this scheme, an electronic neural network encoder and a diffractive optical network decoder are jointly trained using deep learning to transfer the optical information or message of interest around the opaque occlusion of an arbitrary shape.
no code implementations • 12 Apr 2023 • Yuhang Li, Jingxi Li, Yifan Zhao, Tianyi Gan, Jingtian Hu, Mona Jarrahi, Aydogan Ozcan
We demonstrate universal polarization transformers based on an engineered diffractive volume, which can synthesize a large set of arbitrarily-selected, complex-valued polarization scattering matrices between the polarization states at different positions within its input and output field-of-views (FOVs).
no code implementations • 10 Dec 2022 • Deniz Mengu, Anika Tabassum, Mona Jarrahi, Aydogan Ozcan
Moreover, we experimentally demonstrate a diffractive multispectral imager based on a 3D-printed diffractive network that creates at its output image plane a spatially-repeating virtual spectral filter array with 2x2=4 unique bands at terahertz spectrum.
no code implementations • 5 Dec 2022 • Jingxi Li, Tianyi Gan, Yifan Zhao, Bijie Bai, Che-Yung Shen, Songyu Sun, Mona Jarrahi, Aydogan Ozcan
A unidirectional imager would only permit image formation along one direction, from an input field-of-view (FOV) A to an output FOV B, and in the reverse path, the image formation would be blocked.
no code implementations • 21 Jun 2022 • Deniz Mengu, Yifan Zhao, Anika Tabassum, Mona Jarrahi, Aydogan Ozcan
Permutation matrices form an important computational building block frequently used in various fields including e. g., communications, information security and data processing.
no code implementations • 15 Jun 2022 • Cagatay Isil, Deniz Mengu, Yifan Zhao, Anika Tabassum, Jingxi Li, Yi Luo, Mona Jarrahi, Aydogan Ozcan
We report a deep learning-enabled diffractive display design that is based on a jointly-trained pair of an electronic encoder and a diffractive optical decoder to synthesize/project super-resolved images using low-resolution wavefront modulators.
no code implementations • 26 May 2022 • Bijie Bai, Yi Luo, Tianyi Gan, Jingtian Hu, Yuhang Li, Yifan Zhao, Deniz Mengu, Mona Jarrahi, Aydogan Ozcan
Here, we demonstrate a camera design that performs class-specific imaging of target objects with instantaneous all-optical erasure of other classes of objects.
no code implementations • 30 Jun 2020 • Muhammed Veli, Deniz Mengu, Nezih T. Yardimci, Yi Luo, Jingxi Li, Yair Rivenson, Mona Jarrahi, Aydogan Ozcan
Recent advances in deep learning have been providing non-intuitive solutions to various inverse problems in optics.
no code implementations • 23 May 2020 • Deniz Mengu, Yifan Zhao, Nezih T. Yardimci, Yair Rivenson, Mona Jarrahi, Aydogan Ozcan
By modeling the undesired layer-to-layer misalignments in 3D as continuous random variables in the optical forward model, diffractive networks are trained to maintain their inference accuracy over a large range of misalignments; we term this diffractive network design as vaccinated D2NN (v-D2NN).
no code implementations • 15 May 2020 • Jingxi Li, Deniz Mengu, Nezih T. Yardimci, Yi Luo, Xurong Li, Muhammed Veli, Yair Rivenson, Mona Jarrahi, Aydogan Ozcan
3D engineering of matter has opened up new avenues for designing systems that can perform various computational tasks through light-matter interaction.
no code implementations • 14 Sep 2019 • Yi Luo, Deniz Mengu, Nezih T. Yardimci, Yair Rivenson, Muhammed Veli, Mona Jarrahi, Aydogan Ozcan
We report a broadband diffractive optical neural network design that simultaneously processes a continuum of wavelengths generated by a temporally-incoherent broadband source to all-optically perform a specific task learned using deep learning.
no code implementations • 14 Apr 2018 • Xing Lin, Yair Rivenson, Nezih T. Yardimci, Muhammed Veli, Mona Jarrahi, Aydogan Ozcan
We introduce an all-optical Diffractive Deep Neural Network (D2NN) architecture that can learn to implement various functions after deep learning-based design of passive diffractive layers that work collectively.