paper-with-me

Papers

Wavelength-Multiplexed 2D Beam Steering via a Passive Diffractive Network

2026-06-15 · Che-Yung Shen, Yuhang Li, Cagatay Isil, Tianyi Gan, Mona Jarrahi, Aydogan Ozcan arxiv

We introduce a wavelength-addressable diffractive optical network that transforms illumination wavelength into a high-dimensional control parameter for arbitrarily programmable 2D beam steering. The proposed passive architecture comprises cascaded spatially optimized diffractive layers, jointly designed using deep learning, to rapidly map distinct wavelengths to predefined/desired output angles. Unlike conventional single-layer dispersive optical elements, which are physically restricted to 1D linear mapping, this framework harnesses complex wavefront transformations to utilize the illumination wavelength as an intrinsic addressing key for arbitrary 2D beam steering, eliminating the need for mechanical scanning or electronic phase control. We numerically demonstrate wavelength-controlled beam steering across 625 wavelength channels spanning 400-750 nm, realizing a 25 x 25 array of independently addressable beam positions with subwavelength positioning accuracy and high channel fidelity. Unlike conventional gratings, which constrain wavelength routing to a linear trajectory, the proposed diffractive network performs nonlocal wavefront transformations, enabling arbitrary wavelength-to-angle mappings across a 2D field of view. We further validate the proposed framework experimentally in both the terahertz and visible spectral regimes, demonstrating wavelength-multiplexed beam steering using 3D fabricated passive diffractive layers at terahertz frequencies and phase-only spatial light modulators in the visible spectrum. This wavelength-addressable diffractive architecture establishes a compact and scalable paradigm for high-speed programmable beam steering, with potential applications in optical communications, routing, imaging, sensing, and emerging photonic information-processing systems.

📄 PDF Abstract BibTeX arXiv:2606.16261

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Wavelength-multiplexed massively parallel diffractive optical information storage and image projection

2026-04-03 · Che-Yung Shen, Yuhang Li, Cagatay Isil, Jingxi Li 외 arxiv

We introduce a wavelength-multiplexed massively parallel diffractive information storage platform composed of dielectric surfaces that are structurally optimized at the wavelength scale using deep learning to store and p…

Multiplane Quantitative Phase Imaging Using a Wavelength-Multiplexed Diffractive Optical Processor

2024-03-16 · Che-Yung Shen, Jingxi Li, Tianyi Gan, Yuhang Li 외

Quantitative phase imaging (QPI) is a label-free technique that provides optical path length information for transparent specimens, finding utility in biology, materials science, and engineering. Here, we present quantit…

Massively Parallel Universal Linear Transformations using a Wavelength-Multiplexed Diffractive Optical Network

2022-08-13 · Jingxi Li, Bijie Bai, Yi Luo, Aydogan Ozcan

We report deep learning-based design of a massively parallel broadband diffractive neural network for all-optically performing a large group of arbitrarily-selected, complex-valued linear transformations between an input…

Compressive single-pixel imaging via a wavelength-multiplexed spatially incoherent diffractive optical processor

2026-03-23 · Xiao Wang, Yiyang Wu, Yuntian Wang, Md Sadman Sakib Rahman 외 arxiv

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-acquisition times. To address this, we propos…

All-Optical Phase Conjugation Using Diffractive Wavefront Processing

2023-11-08 · Che-Yung Shen, Jingxi Li, Tianyi Gan, Mona Jarrahi 외

Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with various applications ranging from imaging to beam focusing. Here, we present the design of a diffractive wavefro…

AllDeep Learning