Analysis of the influence of antireflective coatings on the diffraction efficiency of diffractive optical elements

Fluder, Grzegorz; Kowalik, Artur; Rojek, Anna; Sobczyk, Artur; Choromański, Zdzisław; Jóźwik, Michał

doi:10.1364/oe.422044

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…However, such conventional optical components have well‐established fabrication technologies supporting their optimized use in a microscope design. With advances in diffractive optical computing, more efficient diffractive surface designs [ 62 ] can be enabled in the future to further increase the output diffraction efficiencies of diffractive networks.…”

Section: Discussionmentioning

confidence: 99%

All‐Optical Phase Recovery: Diffractive Computing for Quantitative Phase Imaging

Mengü

Ozcan

2022

Advanced Optical Materials

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Quantitative phase imaging (QPI) is a label‐free computational imaging technique that provides optical path length information of specimens. In modern implementations, the quantitative phase image of an object is reconstructed digitally through numerical methods running in a computer, often using iterative algorithms. Here, a diffractive QPI network that can perform all‐optical phase recovery is demonstrated, and the quantitative phase image of an object is synthesized by converting the input phase information of a scene into intensity variations at the output plane. A diffractive QPI network is a specialized all‐optical processor designed to perform a quantitative phase‐to‐intensity transformation through passive diffractive surfaces that are spatially engineered using deep learning and image data. Forming a compact, all‐optical network that axially extends only ≈200–300λ, where λ is the illumination wavelength, this framework can replace traditional QPI systems and related digital computational burden with a set of passive transmissive layers. All‐optical diffractive QPI networks can potentially enable power‐efficient, high frame‐rate, and compact phase imaging systems that might be useful for various applications, including, e.g., microscopy and sensing.

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Section: Discussionmentioning

confidence: 99%

All‐Optical Phase Recovery: Diffractive Computing for Quantitative Phase Imaging

Mengü

Ozcan

2022

Advanced Optical Materials

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High-speed measurement method for diffraction efficiency of gratings in broad range wavelength based on AOTF

Xu,

Li,

Jirigalantu

et al. 2024

Opt. Express

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Diffraction efficiency is a critical indicator of grating performance. Traditional single-point measurement methods are slow, often taking several hours to generate a complete diffraction efficiency curve. Existing fast measurement techniques are limited to providing efficiency curves only within the 550–750 nm wavelength range. Therefore, this paper proposes a new high-speed measurement method that leverages an acousto-optic tunable filter (AOTF), an integrating sphere, and a concave mirror to achieve rapid and precise diffraction efficiency measurements. Experimental results demonstrate that for gratings with 300–1200 grooves per millimeter, this method can complete measurements within the 500–1000 nm wavelength range in under one minute. The mean absolute error is less than 2%, with a repeatability error also below 2%.

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Multilevel Diffractive Lenses: Recent Advances and Applications

Shi,

Zhao,

Chen

et al. 2024

Symmetry

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Multilevel diffractive lenses (MDLs) has undergone considerable advancements, marked by their exceptional efficiency and diverse focusing capabilities, resulting in their widespread use in optical systems. In recent times, MDLs have consistently been juxtaposed with metalenses, which have experienced swift progress over the last decade. Concurrently, MDLs have continued to evolve, propelled by their distinct advantages, such as cost-effective production and adaptability for mass manufacturing. This article explores the evolution and foundational concepts of MDLs, highlighting the advantages of their circular symmetry in enhancing simulation and optimization efficiency. Furthermore, we present several innovative fabrication methods for MDLs that capitalize on the latest advancements in 3D printing technology. We also show the practical applications and potential future developments of MDLs.

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Analysis of the influence of antireflective coatings on the diffraction efficiency of diffractive optical elements

Cited by 3 publications

References 16 publications

All‐Optical Phase Recovery: Diffractive Computing for Quantitative Phase Imaging

All‐Optical Phase Recovery: Diffractive Computing for Quantitative Phase Imaging

High-speed measurement method for diffraction efficiency of gratings in broad range wavelength based on AOTF

Multilevel Diffractive Lenses: Recent Advances and Applications

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