8 papers
Universal Function Approximation via Diffractive Optical Processors: Physical Limits, Error Bounds, and Learnability
Md Sadman Sakib Rahman, Che-Yung Shen, Aydogan Ozcan
We present a unified theoretical framework connecting classical universal approximation theory, Fourier-feature approximation, and diffractive optical processors. We show that phas…
Breaking the Cascade: Compact Nonlinear Optical Computing with Single-Layer Encoder-Decoder Co-Localization
Yuntian Wang, Alexander Chen, Md Sadman Sakib Rahman +1
We demonstrate that nonlinear computing can be achieved with a single linear diffractive surface under coherent illumination. We introduce a compact encoder-decoder co-localization…
Large-scale nonlinear optical computing with incoherent light via linear diffractive systems
Alexander Chen, Yuntian Wang, Md Sadman Sakib Rahman +2
Nonlinear computation is essential for various information processing tasks. Optical implementations are attractive because passive light propagation can manipulate high-dimensiona…
Compressive single-pixel imaging via a wavelength-multiplexed spatially incoherent diffractive optical processor
Xiao Wang, Yiyang Wu, Yuntian Wang +8
Despite offering high sensitivity, a high signal-to-noise ratio, and a broad spectral range, single-pixel imaging (SPI) is limited by low measurement efficiency and long data-acqui…
Programming of refractive functions
Md Sadman Sakib Rahman, Tianyi Gan, Mona Jarrahi +1
Snell's law dictates the phenomenon of light refraction at the interface between two media. Here, we demonstrate arbitrary programming of light refraction through an engineered mat…
Massively parallel and universal approximation of nonlinear functions using diffractive processors
Md Sadman Sakib Rahman, Yuhang Li, Xilin Yang +2
Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak…