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Holography, Gratings, and Diffraction|26 Article(s)
Phase space framework enables a variable-scale diffraction model for coherent imaging and display
Zhi Li, Xuhao Luo, Jing Wang, Xin Yuan, Dongdong Teng, Qiang Song, and Huigao Duan
The fast algorithms in Fourier optics have invigorated multifunctional device design and advanced imaging technologies. However, the necessity for fast computations limits the widely used conventional Fourier methods, where the image plane has a fixed size at certain diffraction distances. These limitations pose challenges in intricate scaling transformations, 3D reconstructions, and full-color displays. Currently, the lack of effective solutions makes people often resort to pre-processing that compromises fidelity. In this paper, leveraging a higher-dimensional phase space method, a universal framework is proposed for customized diffraction calculation methods. Within this framework, a variable-scale diffraction computation model is established for adjusting the size of the image plane and can be operated by fast algorithms. The model’s robust variable-scale capabilities and its aberration automatic correction capability are validated for full-color holography, and high fidelity is achieved. The tomography experiments demonstrate that this model provides a superior solution for holographic 3D reconstruction. In addition, this model is applied to achieve full-color metasurface holography with near-zero crosstalk, showcasing its versatile applicability at nanoscale. Our model presents significant prospects for applications in the optics community, such as beam shaping, computer-generated holograms (CGHs), augmented reality (AR), metasurface optical elements (MOEs), and advanced holographic head-up display (HUD) systems. The fast algorithms in Fourier optics have invigorated multifunctional device design and advanced imaging technologies. However, the necessity for fast computations limits the widely used conventional Fourier methods, where the image plane has a fixed size at certain diffraction distances. These limitations pose challenges in intricate scaling transformations, 3D reconstructions, and full-color displays. Currently, the lack of effective solutions makes people often resort to pre-processing that compromises fidelity. In this paper, leveraging a higher-dimensional phase space method, a universal framework is proposed for customized diffraction calculation methods. Within this framework, a variable-scale diffraction computation model is established for adjusting the size of the image plane and can be operated by fast algorithms. The model’s robust variable-scale capabilities and its aberration automatic correction capability are validated for full-color holography, and high fidelity is achieved. The tomography experiments demonstrate that this model provides a superior solution for holographic 3D reconstruction. In addition, this model is applied to achieve full-color metasurface holography with near-zero crosstalk, showcasing its versatile applicability at nanoscale. Our model presents significant prospects for applications in the optics community, such as beam shaping, computer-generated holograms (CGHs), augmented reality (AR), metasurface optical elements (MOEs), and advanced holographic head-up display (HUD) systems.
Photonics Research
- Publication Date: Aug. 29, 2024
- Vol. 12, Issue 9, 1937 (2024)
Programmable meta-holography dynamics enabled by grating-modulation
Runlong Rao, Shuai Wan, Zhe Li, Yangyang Shi, and Zhongyang Li
Towards next-generation intelligent display devices, it is urgent to find a cheap and convenient dynamic optical control method. Conventional gratings are widely used as cheap diffractive elements due to their effective optical control capabilities. However, they are limited within multi-function or complex optical modulation due to the lack of accurate control of the amplitude/phase at pixel-level. Here, a metasurface-assisted grating-modulation system is originally proposed to achieve switchable multi-fold meta-holographic dynamics. By incorporating metasurfaces with traditional gratings and tuning their relative coupling positions, the modulation system gains the optical modulation capability to realize complex optical functionalities. Specifically, by varying the grating periods/positions relative to the metasurface, 2–8 holographic image channels are programmed to be dynamically exhibited and switched. The proposed metasurface-assisted grating-modulation approach enjoys cost-effective convenience, strong encoding freedom, and facile operation, which promises programmable optical displays, optical sensors, optical information encryption/storage, etc. Towards next-generation intelligent display devices, it is urgent to find a cheap and convenient dynamic optical control method. Conventional gratings are widely used as cheap diffractive elements due to their effective optical control capabilities. However, they are limited within multi-function or complex optical modulation due to the lack of accurate control of the amplitude/phase at pixel-level. Here, a metasurface-assisted grating-modulation system is originally proposed to achieve switchable multi-fold meta-holographic dynamics. By incorporating metasurfaces with traditional gratings and tuning their relative coupling positions, the modulation system gains the optical modulation capability to realize complex optical functionalities. Specifically, by varying the grating periods/positions relative to the metasurface, 2–8 holographic image channels are programmed to be dynamically exhibited and switched. The proposed metasurface-assisted grating-modulation approach enjoys cost-effective convenience, strong encoding freedom, and facile operation, which promises programmable optical displays, optical sensors, optical information encryption/storage, etc.
Photonics Research
- Publication Date: Jul. 01, 2024
- Vol. 12, Issue 7, 1522 (2024)
Wide-angle digital holography with aliasing-free recording
Rafał Kukołowicz, Izabela Gerej, and Tomasz Kozacki
High-quality wide-angle holographic content is at the heart of the success of near-eye display technology. This work proposes the first digital holographic (DH) system enabling recording wide-angle scenes assembled from objects larger than the setup field of view (FOV), which can be directly replayed without 3D deformation in the near-eye display. The hologram formation in the DH system comprises free space propagation and Fourier transform (FT), which are connected by a rectangular aperture. First, the object wave propagates in free space to the rectangular aperture. Then, the band-limited wavefield is propagated through the single lens toward the camera plane. The rectangular aperture can take two sizes, depending on which DH operates in off-axis or phase-shifting recording mode. An integral part of the DH solution is a numerical reconstruction algorithm consisting of two elements: fringe processing for object wave recovery and wide-angle propagation to the object plane. The second element simulates propagation through both parts of the experimental system. The free space part is a space-limited angular spectrum compact space algorithm, while for propagation through the lens, the piecewise FT algorithm with Petzval curvature compensation is proposed. In the experimental part of the paper, we present the wide-angle DH system with FOV 25°×19°, which allows high-quality recording and reconstruction of large complex scenes. High-quality wide-angle holographic content is at the heart of the success of near-eye display technology. This work proposes the first digital holographic (DH) system enabling recording wide-angle scenes assembled from objects larger than the setup field of view (FOV), which can be directly replayed without 3D deformation in the near-eye display. The hologram formation in the DH system comprises free space propagation and Fourier transform (FT), which are connected by a rectangular aperture. First, the object wave propagates in free space to the rectangular aperture. Then, the band-limited wavefield is propagated through the single lens toward the camera plane. The rectangular aperture can take two sizes, depending on which DH operates in off-axis or phase-shifting recording mode. An integral part of the DH solution is a numerical reconstruction algorithm consisting of two elements: fringe processing for object wave recovery and wide-angle propagation to the object plane. The second element simulates propagation through both parts of the experimental system. The free space part is a space-limited angular spectrum compact space algorithm, while for propagation through the lens, the piecewise FT algorithm with Petzval curvature compensation is proposed. In the experimental part of the paper, we present the wide-angle DH system with FOV 25°×19°, which allows high-quality recording and reconstruction of large complex scenes.
Photonics Research
- Publication Date: May. 01, 2024
- Vol. 12, Issue 5, 1098 (2024)
Long distance all-optical logic operations through a single multimode fiber empowered by wavefront shaping|Editors' Pick
Zhipeng Yu, Tianting Zhong, Huanhao Li, Haoran Li, Chi Man Woo, Shengfu Cheng, Shuming Jiao, Honglin Liu, Chao Lu, and Puxiang Lai
Multimode fibers (MMFs) are a promising solution for high-throughput signal transmission in the time domain. However, crosstalk among different optical modes within the MMF scrambles input information and creates seemingly random speckle patterns at the output. To characterize this process, a transmission matrix (TM) can be used to relate input and output fields. Recent innovations use TMs to manipulate the output field by shaping the input wavefront for exciting advances in deep-brain imaging, neuron stimulation, quantum networks, and analog operators. However, these approaches consider input/output segments as independent, limiting their use for separate signal processing, such as logic operations. Our proposed method, which makes input/output segments as interdependent, adjusts the phase of corresponding output fields using phase bias maps superimposed on input segments. Coherent superposition enables signal logic operations through a 15-m-long MMF. In experiments, a single optical logic gate containing three basic logic functions and cascading multiple logic gates to handle binary operands is demonstrated. Bitwise operations are performed for multi-bit logic operations, and multiple optical logic gates are reconstructed simultaneously in a single logic gate with polarization multiplexing. The proposed method may open new avenues for long-range logic signal processing and transmission via MMFs. Multimode fibers (MMFs) are a promising solution for high-throughput signal transmission in the time domain. However, crosstalk among different optical modes within the MMF scrambles input information and creates seemingly random speckle patterns at the output. To characterize this process, a transmission matrix (TM) can be used to relate input and output fields. Recent innovations use TMs to manipulate the output field by shaping the input wavefront for exciting advances in deep-brain imaging, neuron stimulation, quantum networks, and analog operators. However, these approaches consider input/output segments as independent, limiting their use for separate signal processing, such as logic operations. Our proposed method, which makes input/output segments as interdependent, adjusts the phase of corresponding output fields using phase bias maps superimposed on input segments. Coherent superposition enables signal logic operations through a 15-m-long MMF. In experiments, a single optical logic gate containing three basic logic functions and cascading multiple logic gates to handle binary operands is demonstrated. Bitwise operations are performed for multi-bit logic operations, and multiple optical logic gates are reconstructed simultaneously in a single logic gate with polarization multiplexing. The proposed method may open new avenues for long-range logic signal processing and transmission via MMFs.
Photonics Research
- Publication Date: Mar. 01, 2024
- Vol. 12, Issue 3, 587 (2024)
Physics-aware cross-domain fusion aids learning-driven computer-generated holography
Ganzhangqin Yuan, Mi Zhou, Fei Liu, Mu Ku Chen, Kui Jiang, Yifan Peng, and Zihan Geng
The rapid advancement of computer-generated holography has bridged deep learning with traditional optical principles in recent years. However, a critical challenge in this evolution is the efficient and accurate conversion from the amplitude to phase domain for high-quality phase-only hologram (POH) generation. Existing computational models often struggle to address the inherent complexities of optical phenomena, compromising the conversion process. In this study, we present the cross-domain fusion network (CDFN), an architecture designed to tackle the complexities involved in POH generation. The CDFN employs a multi-stage (MS) mechanism to progressively learn the translation from amplitude to phase domain, complemented by the deep supervision (DS) strategy of middle features to enhance task-relevant feature learning from the initial stages. Additionally, we propose an infinite phase mapper (IPM), a phase-mapping function that circumvents the limitations of conventional activation functions and encapsulates the physical essence of holography. Through simulations, our proposed method successfully reconstructs high-quality 2K color images from the DIV2K dataset, achieving an average PSNR of 31.68 dB and SSIM of 0.944. Furthermore, we realize high-quality color image reconstruction in optical experiments. The experimental results highlight the computational intelligence and optical fidelity achieved by our proposed physics-aware cross-domain fusion. The rapid advancement of computer-generated holography has bridged deep learning with traditional optical principles in recent years. However, a critical challenge in this evolution is the efficient and accurate conversion from the amplitude to phase domain for high-quality phase-only hologram (POH) generation. Existing computational models often struggle to address the inherent complexities of optical phenomena, compromising the conversion process. In this study, we present the cross-domain fusion network (CDFN), an architecture designed to tackle the complexities involved in POH generation. The CDFN employs a multi-stage (MS) mechanism to progressively learn the translation from amplitude to phase domain, complemented by the deep supervision (DS) strategy of middle features to enhance task-relevant feature learning from the initial stages. Additionally, we propose an infinite phase mapper (IPM), a phase-mapping function that circumvents the limitations of conventional activation functions and encapsulates the physical essence of holography. Through simulations, our proposed method successfully reconstructs high-quality 2K color images from the DIV2K dataset, achieving an average PSNR of 31.68 dB and SSIM of 0.944. Furthermore, we realize high-quality color image reconstruction in optical experiments. The experimental results highlight the computational intelligence and optical fidelity achieved by our proposed physics-aware cross-domain fusion.
Photonics Research
- Publication Date: Nov. 13, 2024
- Vol. 12, Issue 12, 2747 (2024)
Speckle-free holography with a diffraction-aware global perceptual model
Yiran Wei, Yiyun Chen, Mi Zhou, Mu Ku Chen, Shuming Jiao, Qinghua Song, Xiao-Ping Zhang, and Zihan Geng
Computer-generated holography (CGH) based on neural networks has been actively investigated in recent years, and convolutional neural networks (CNNs) are frequently adopted. A convolutional kernel captures local dependencies between neighboring pixels. However, in CGH, each pixel on the hologram influences all the image pixels on the observation plane, thus requiring a network capable of learning long-distance dependencies. To tackle this problem, we propose a CGH model called Holomer. Its single-layer perceptual field is 43 times larger than that of a widely used 3×3 convolutional kernel, thanks to the embedding-based feature dimensionality reduction and multi-head sliding-window self-attention mechanisms. In addition, we propose a metric to measure the networks’ learning ability of the inverse diffraction process. In the simulation, our method demonstrated noteworthy performance on the DIV2K dataset at a resolution of 1920×1024, achieving a PSNR and an SSIM of 35.59 dB and 0.93, respectively. The optical experiments reveal that our results have excellent image details and no observable background speckle noise. This work paves the path of high-quality hologram generation. Computer-generated holography (CGH) based on neural networks has been actively investigated in recent years, and convolutional neural networks (CNNs) are frequently adopted. A convolutional kernel captures local dependencies between neighboring pixels. However, in CGH, each pixel on the hologram influences all the image pixels on the observation plane, thus requiring a network capable of learning long-distance dependencies. To tackle this problem, we propose a CGH model called Holomer. Its single-layer perceptual field is 43 times larger than that of a widely used 3×3 convolutional kernel, thanks to the embedding-based feature dimensionality reduction and multi-head sliding-window self-attention mechanisms. In addition, we propose a metric to measure the networks’ learning ability of the inverse diffraction process. In the simulation, our method demonstrated noteworthy performance on the DIV2K dataset at a resolution of 1920×1024, achieving a PSNR and an SSIM of 35.59 dB and 0.93, respectively. The optical experiments reveal that our results have excellent image details and no observable background speckle noise. This work paves the path of high-quality hologram generation.
Photonics Research
- Publication Date: Oct. 10, 2024
- Vol. 12, Issue 11, 2418 (2024)
Multi-plane vectorial holography based on a height tunable metasurface fabricated by femtosecond laser direct writing
Chao Liu, Hongbo Wang, Ruizhe Zhao, Yuhao Lei, Shumin Dong, Yujin Cai, Wang Zhou, Yongtian Wang, Lingling Huang, and Ke-Mi Xu
Metasurfaces have prompted the transformation from the investigation of scalar holography to vectorial holography and led various applications in vectorial optical field manipulation. However, the majority of previously demonstrated methods focused on the reconstruction of a vectorial holographic image located at a predefined individual image plane. The evolution of polarization transformation during propagation can provide more design freedoms for realizing three-dimensional holography with complicated polarization feature. Here, we demonstrated a Jones matrix framework to generate vectorial holographic images with continuously varied polarization distributions at multiple different image planes based on a height tunable metasurface. The proposed metasurface is composed of IP-L (a type of photoresist) nanofins with different lengths, widths, heights, as well as orientation angles fabricated by femtosecond laser direct writing. Such a fabrication method is in favor of 3D arbitrary structure processing, large area fabrication, as well as fabrication on curved substrates. Meanwhile, it is easy to fabricate structures that can be integrated with other devices, including optical fibers, photodetectors, and complementary metal–oxide semiconductors. Our demonstrated method provides a feasible way to generate high-dimensional vectorial fields with longitudinally varied features from the perspective of holography and can be used in the related areas including optical trapping, sensing, and imaging. Metasurfaces have prompted the transformation from the investigation of scalar holography to vectorial holography and led various applications in vectorial optical field manipulation. However, the majority of previously demonstrated methods focused on the reconstruction of a vectorial holographic image located at a predefined individual image plane. The evolution of polarization transformation during propagation can provide more design freedoms for realizing three-dimensional holography with complicated polarization feature. Here, we demonstrated a Jones matrix framework to generate vectorial holographic images with continuously varied polarization distributions at multiple different image planes based on a height tunable metasurface. The proposed metasurface is composed of IP-L (a type of photoresist) nanofins with different lengths, widths, heights, as well as orientation angles fabricated by femtosecond laser direct writing. Such a fabrication method is in favor of 3D arbitrary structure processing, large area fabrication, as well as fabrication on curved substrates. Meanwhile, it is easy to fabricate structures that can be integrated with other devices, including optical fibers, photodetectors, and complementary metal–oxide semiconductors. Our demonstrated method provides a feasible way to generate high-dimensional vectorial fields with longitudinally varied features from the perspective of holography and can be used in the related areas including optical trapping, sensing, and imaging.
Photonics Research
- Publication Date: Sep. 16, 2024
- Vol. 12, Issue 10, 2158 (2024)
Holographic acoustic-signal authenticator
Sudheesh K. Rajput, Allarakha Shikder, Naveen K. Nishchal, Ryuju Todo, Osamu Matoba, and Yasuhiro Awatsuji
Most optical information processors deal with text or image data, and it is very difficult to deal experimentally with acoustic data. Therefore, optical advances that deal with acoustic data are highly desirable in this area. In particular, the development of a voice or acoustic-signal authentication technique using optical correlation can open a new line of research in the field of optical security and could also provide a tool for other applications where comparison of acoustic signals is required. Here, we report holographic acoustic-signal authentication by integrating the holographic microphone recording with optical correlation to meet some of the above requirements. The reported method avails the flexibility of 3D visualization of acoustic signals at sensitive locations and parallelism offered by an optical correlator/processor. We demonstrate text-dependent optical voice correlation that can determine the authenticity of acoustic signal by discarding or accepting it in accordance with the reference signal. The developed method has applications in security screening and industrial quality control. Most optical information processors deal with text or image data, and it is very difficult to deal experimentally with acoustic data. Therefore, optical advances that deal with acoustic data are highly desirable in this area. In particular, the development of a voice or acoustic-signal authentication technique using optical correlation can open a new line of research in the field of optical security and could also provide a tool for other applications where comparison of acoustic signals is required. Here, we report holographic acoustic-signal authentication by integrating the holographic microphone recording with optical correlation to meet some of the above requirements. The reported method avails the flexibility of 3D visualization of acoustic signals at sensitive locations and parallelism offered by an optical correlator/processor. We demonstrate text-dependent optical voice correlation that can determine the authenticity of acoustic signal by discarding or accepting it in accordance with the reference signal. The developed method has applications in security screening and industrial quality control.
Photonics Research
- Publication Date: Sep. 06, 2024
- Vol. 12, Issue 10, 2104 (2024)
Dynamic multifunctional metasurfaces: an inverse design deep learning approach
Zhi-Dan Lei, Yi-Duo Xu, Cheng Lei, Yan Zhao, and Du Wang
Optical metasurfaces (OMs) offer unprecedented control over electromagnetic waves, enabling advanced optical multiplexing. The emergence of deep learning has opened new avenues for designing OMs. However, existing deep learning methods for OMs primarily focus on forward design, which limits their design capabilities, lacks global optimization, and relies on prior knowledge. Additionally, most OMs are static, with fixed functionalities once processed. To overcome these limitations, we propose an inverse design deep learning method for dynamic OMs. Our approach comprises a forward prediction network and an inverse retrieval network. The forward prediction network establishes a mapping between meta-unit structure parameters and reflectance spectra. The inverse retrieval network generates a library of meta-unit structure parameters based on target requirements, enabling end-to-end design of OMs. By incorporating the dynamic tunability of the phase change material Sb2Te3 with inverse design deep learning, we achieve the design and verification of dynamic multifunctional OMs. Our results demonstrate OMs with multiple information channels and encryption capabilities that can realize multiple physical field optical modulation functions. When Sb2Te3 is in the amorphous state, near-field nano-printing based on meta-unit amplitude modulation is achieved for X-polarized incident light, while holographic imaging based on meta-unit phase modulation is realized for circularly polarized light. In the crystalline state, the encrypted information remains secure even with the correct polarization input, achieving double encryption. This research points towards ultra-compact, high-capacity, and highly secure information storage approaches. Optical metasurfaces (OMs) offer unprecedented control over electromagnetic waves, enabling advanced optical multiplexing. The emergence of deep learning has opened new avenues for designing OMs. However, existing deep learning methods for OMs primarily focus on forward design, which limits their design capabilities, lacks global optimization, and relies on prior knowledge. Additionally, most OMs are static, with fixed functionalities once processed. To overcome these limitations, we propose an inverse design deep learning method for dynamic OMs. Our approach comprises a forward prediction network and an inverse retrieval network. The forward prediction network establishes a mapping between meta-unit structure parameters and reflectance spectra. The inverse retrieval network generates a library of meta-unit structure parameters based on target requirements, enabling end-to-end design of OMs. By incorporating the dynamic tunability of the phase change material Sb2Te3 with inverse design deep learning, we achieve the design and verification of dynamic multifunctional OMs. Our results demonstrate OMs with multiple information channels and encryption capabilities that can realize multiple physical field optical modulation functions. When Sb2Te3 is in the amorphous state, near-field nano-printing based on meta-unit amplitude modulation is achieved for X-polarized incident light, while holographic imaging based on meta-unit phase modulation is realized for circularly polarized light. In the crystalline state, the encrypted information remains secure even with the correct polarization input, achieving double encryption. This research points towards ultra-compact, high-capacity, and highly secure information storage approaches.
Photonics Research
- Publication Date: Dec. 22, 2023
- Vol. 12, Issue 1, 123 (2024)
High-speed rendering pipeline for polygon-based holograms
Fan Wang, Tomoyoshi Ito, and Tomoyoshi Shimobaba
As an important three-dimensional (3D) display technology, computer-generated holograms (CGHs) have been facing challenges of computational efficiency and realism. The polygon-based method, as the mainstream CGH algorithm, has been widely studied and improved over the past 20 years. However, few comprehensive and high-speed methods have been proposed. In this study, we propose an analytical spectrum method based on the principle of spectral energy concentration, which can achieve a speedup of nearly 30 times and generate high-resolution (8K) holograms with low memory requirements. Based on the Phong illumination model and the sub-triangles method, we propose a shading rendering algorithm to achieve a very smooth and realistic reconstruction with only a small increase in computational effort. Benefiting from the idea of triangular subdivision and octree structures, the proposed original occlusion culling scheme can closely crop the overlapping areas with almost no additional overhead, thus rendering a 3D parallax sense. With this, we built a comprehensive high-speed rendering pipeline of polygon-based holograms capable of computing any complex 3D object. Numerical and optical reconstructions confirmed the generalizability of the pipeline. As an important three-dimensional (3D) display technology, computer-generated holograms (CGHs) have been facing challenges of computational efficiency and realism. The polygon-based method, as the mainstream CGH algorithm, has been widely studied and improved over the past 20 years. However, few comprehensive and high-speed methods have been proposed. In this study, we propose an analytical spectrum method based on the principle of spectral energy concentration, which can achieve a speedup of nearly 30 times and generate high-resolution (8K) holograms with low memory requirements. Based on the Phong illumination model and the sub-triangles method, we propose a shading rendering algorithm to achieve a very smooth and realistic reconstruction with only a small increase in computational effort. Benefiting from the idea of triangular subdivision and octree structures, the proposed original occlusion culling scheme can closely crop the overlapping areas with almost no additional overhead, thus rendering a 3D parallax sense. With this, we built a comprehensive high-speed rendering pipeline of polygon-based holograms capable of computing any complex 3D object. Numerical and optical reconstructions confirmed the generalizability of the pipeline.
Photonics Research
- Publication Date: Feb. 01, 2023
- Vol. 11, Issue 2, 313 (2023)
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