Scalability of all-optical neural networks based on spatial light modulators

Author(s):

Ying Zuo, Zhao Yujun, You-Chiuan Chen, Shengwang Du & Liu, Junwei

Abstract:

“Optical implementation of artificial neural networks has been attracting great attention due to its potential in parallel computation at speed of light. Although all-optical deep neural networks (AODNNs) with a few neurons have been experimentally demonstrated with acceptable errors re- cently, the feasibility of large scale AODNNs remains unknown because error might accumulate inevitably with increasing number of neurons and connections. Here, we demonstrate a scalable AODNN with programmable linear operations and tunable nonlinear activation functions. We ver- ify its scalability by measuring and analyzing errors propagating from a single neuron to the entire network. The feasibility of AODNNs is further confirmed by recognizing handwritten digits and fashions respectively.”

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Publication: Physical Review Applied
Issue/Year: Physical Review Applied, 2021
DOI: https://doi.org/10.1103/PhysRevApplied.15.054034

LCOS Spatial Light Modulators for color-sequential holographic applications

all Holoeye special light modulatorsHOLOEYE offers three fast Spatial Light Modulator models, which are capable of color sequential phase operation. The LETO-3, LUNA and PLUTO-2.1 devices can address 3 x 8 bit within a frame (180 Hz) using fast display versions for the visible range. The three HD resolution (1920 x 1080 pixel) SLMs also feature an RGB light source sync connector on the driver board for use with RGB color-switchable laser sources.
The LETO-3 SLM has a resolution of 1920 x 1080 pixels with 6.4 µm pixel pitch. (more…)

Precise position and angular control of optical trapping and manipulation via a single vortex-pair beam

Author(s):

Jisen Wen, Binjie Gao, Guiyuan Zhu, DadongLiu, Li-GangWang

Abstract:

“Optical trapping and manipulation using structured laser beams now attract increasing attention in many areas including biology, atomic science, and nanofabrication. Here we propose and demonstrate experimentally the use of a single vortex-pair beam in two-dimensional optical trapping and manipulation. Using the focal properties of such vortex-pair beams, we successfully manipulate two spherical microparticles simultaneously, and obtain the precise position-control on the microparticles by adjusting the off-axis parameter of the vortex-pair beam. Furthermore, we also realize the high-precision angular-controllable rotation of cylindrical microrods by rotating the initial phase structure of such vortex-pair beams, which is like an optical wrench due to two focused bright spots at the focal plane of objective lens. Our experimental result provides an alternative manipulation of microparticles and may have potential applications in biological area, and optically driven micromachines or motors.”

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Publication: Optics and Lasers in Engineering
Issue/Year: Optics and Lasers in Engineering, Volume 148, 106773 (2022)
DOI: 10.1016/j.optlaseng.2021.106773

High-Flexibility Control of Structured Light with Combined Adaptive Optical Systems

Author(s):

Grunwald, Rüdiger; Jurke, Mathias; Bock, Martin; Liebmann, Max; Bruno, Binal Poyyathuruthy; Gowda, Hitesh & Wallrabe, Ulrike

Abstract:

“Combining the specific advantages of high-resolution liquid-crystal-on-silicon spatial light modulators (LCoS-SLMs) and reflective or refractive micro-electro-mechanical systems (MEMS) presents new prospects for the generation of structured light fields. In particular, adaptive self-apodization schemes can significantly reduce diffraction by low-loss spatial filtering. The concept enables one to realize low-dispersion shaping of nondiffracting femtosecond wavepackets and to temporally switch, modulate or deflect spatially structured beams. Adaptive diffraction management by structured illumination is demonstrated for piezo-based and thermally actuated axicons, spiral phase plates (SPPs) and Fresnel bi-mirrors. Improved non-collinear autocorrelation with angular-tunable Fresnel-bi-mirrors via self-apodized illumination and phase contrast of an SLM is proposed. An extension of the recently introduced nondiffractive Talbot effect to a tunable configuration by combining an SLM and a fluid lens is reported. Experimental results for hexagonal as well as orthogonal array beams are presented.”

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Publication: Photonics
Issue/Year: Photonics, Volume 9; Number 1; Pages 42; 2022
DOI: 10.3390/photonics9010042

Electro-Optic Modulation of Higher-Order Poincar’e Beam Based on Nonlinear Optical Crystal

Author(s):

Han, Lu; Li, Zhan; Chen, Chao; Sun, Xin; Zhang, Junyong & Liu, Dean

Abstract:

“Vector beams (VBs) have spatially inhomogeneous polarization states distribution and have been widely used in many fields. In this paper, we proposed a method to modulate polarization states of higher-order Poincaré (HOP) beams and designed a system based on Mach-Zehnder interferometers, in which polarization state (include azimuth and ellipticity) of generated HOP beams were modulated by linear electro-optic (EO) effect of nonlinear optical crystals. Using this method, the polarization state of generated HOP beams could be controlled by voltage signal applied on EO crystals, which makes the process of the polarization state change with no optical element moving and mechanical vibrations. Besides, due to the flexibility of the voltage signal, the polarization state could be switched directly and immediately.”

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Publication: Photonics
Issue/Year: Photonics, Volume 9; Number 1; Pages 41; 2022
DOI: 10.3390/photonics9010041

Dual-task convolutional neural network based on the combination of the U-Net and a diffraction propagation model for phase hologram design with suppressed speckle noise

Author(s):

Sun, Xiuhui; Mu, Xingyu; Xu, Cheng; Pang, Hui; Deng, Qiling; Zhang, Ke; Jiang, Haibo; Du, Jinglei; Yin, Shaoyun & Du, Chunlei

Abstract:

“In this paper, a dual-task convolutional neural network based on the combination of the U-Net and a diffraction propagation model is proposed for the design of phase holograms to suppress speckle noise of the reconstructed images. By introducing a Fresnel transmission layer, based on angular spectrum diffraction theory, as the diffraction propagation model and incorporating it into U-Net as the output layer, the proposed neural network model can describe the actual physical process of holographic imaging, and the distributions of both the light amplitude and phase can be generated. Afterwards, by respectively using the Pearson correlation coefficient (PCC) as the loss function to modulate the distribution of the amplitude, and a proposed target-weighted standard deviation (TWSD) as the loss function to limit the randomness and arbitrariness of the reconstructed phase distribution, the dual tasks of the amplitude reconstruction and phase smoothing are jointly solved, and thus the phase hologram that can produce high quality image without speckle is obtained. Both simulations and optical experiments are carried out to confirm the feasibility and effectiveness of the proposed method. Furthermore, the depth of field (DOF) of the image using the proposed method is much larger than that of using the traditional Gerchberg-Saxton (GS) algorithm due to the smoothness of the reconstructed phase distribution, which is also verified in the experiments. This study provides a new phase hologram design approach and shows the potential of neural networks in the field of the holographic imaging and more.”

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Publication: Optics Express
Issue/Year: Optics Express, Volume 30; Number 2; Pages 2646; 2022
DOI: 10.1364/oe.440956

Discretized continuous quantum-mechanical observables that are neither continuous nor discrete

Author(s):

Thais L. Silva, Łukasz Rudnicki, Daniel S. Tasca, and Stephen P. Walborn

Abstract:

“Most of the fundamental characteristics of quantum mechanics, such as nonlocality and contextuality, are manifest in discrete, finite-dimensional systems. However, many quantum information tasks that exploit these properties cannot be directly adapted to continuous variable systems. To access these quantum features, continuous quantum variables can be made discrete by binning together their different values, resulting in observables with a finite number, d, of outcomes. While direct measurement indeed confirms their manifestly discrete character, here we employ a salient feature of quantum physics known as mutual unbiasedness to show that such coarse-grained observables are in a sense neither continuous nor discrete. Depending on d, the observables can reproduce either the discrete or the continuous behavior, or neither. To illustrate these results, we present an example for the construction of such measurements and employ it in an optical experiment confirming the existence of four mutually unbiased measurements with d=3 outcomes in a continuous variable system, surpassing the number of mutually unbiased continuous variable observables.”

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Publication: Physical Review Research
Issue/Year: Physical Review Research, Volume 4; Number 1; Pages 013060; 2022
DOI: 10.1103/physrevresearch.4.013060

Polygon-based computer-generated holography: a review of fundamentals and recent progress [Invited]

Author(s):

Zhang, Yaping; Fan, Houxin; Wang, Fan; Gu, Xianfeng; Qian, Xiaofan & Poon, Ting-Chung

Abstract:

“In this review paper, we first provide comprehensive tutorials on two classical methods of polygon-based computer-generated holography: the traditional method (also called the fast-Fourier-transform-based method) and the analytical method. Indeed, other modern polygon-based methods build on the idea of the two methods. We will then present some selective methods with recent developments and progress and compare their computational reconstructions in terms of calculation speed and image quality, among other things. Finally, we discuss and propose a fast analytical method called the fast 3D affine transformation method, and based on the method, we present a numerical reconstruction of a computer-generated hologram (CGH) of a 3D surface consisting of 49,272 processed polygons of the face of a real person without the use of graphic processing units; to the best of our knowledge, this represents a state-of-the-art numerical result in polygon-based computed-generated holography. Finally, we also show optical reconstructions of such a CGH and another CGH of the Stanford bunny of 59,996 polygons with 31,724 processed polygons after back-face culling. We hope that this paper will bring out some of the essence of polygon-based computer-generated holography and provide some insights for future research.”

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Publication: Applied Optics
Issue/Year: Applied Optics, Volume 61; Number 5; Pages B363; 2022
DOI: 10.1364/ao.444973

Shapeshifting Diffractive Optical Devices

Author(s):

Oscurato, Stefano L.; Reda, Francesco; Salvatore, Marcella; Borbone, Fabio; Maddalena, Pasqualino & Ambrosio, Antonio

Abstract:

“In optical devices like diffraction gratings and Fresnel lenses, light wavefront is engineered through the structuring of device surface morphology, within thicknesses comparable to the light wavelength. Fabrication of such diffractive optical elements involves highly accurate multistep lithographic processes that in fact set into stone both the surface morphology and optical functionality, resulting in intrinsically static devices. In this work, this fundamental limitation is overcome by introducing shapeshifting diffractive optical elements directly written on an erasable photoresponsive material, whose morphology can be changed in real time to provide different on-demand optical functionalities. First a lithographic configuration that allows writing/erasing cycles of aligned optical elements directly in the light path is developed. Then, the realization of complex diffractive gratings with arbitrary combinations of grating vectors is shown. Finally, a shapeshifting diffractive lens that is reconfigured in the light-path in order to change the imaging parameters of an optical system is demonstrated. The approach leapfrogs the state-of-the-art realization of optical Fourier surfaces by adding on-demand reconfiguration to the potential use in emerging areas in photonics, like transformation and planar optics.”

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Publication: Laser & Photonics Reviews
Issue/Year: Laser & Photonics Reviews, Volume 16; Number 4; Pages 2100514; 2022
DOI: 10.1002/lpor.202100514

Imaging lidar prototype with homography and deep learning ranging methods

Author(s):

Kim, Sehyeon; Chen, Zhaowei & Alisafaee, Hossein

Abstract:

“We report on developing a non-scanning laser-based imaging lidar system based on a diffractive optical element with potential applications in advanced driver assistance systems, autonomous vehicles, drone navigation, and mobile devices. Our proposed lidar utilizes image processing, homography, and deep learning. Our emphasis in the design approach is on the compactness and cost of the final system for it to be deployable both as standalone and complementary to existing lidar sensors, enabling fusion sensing in the applications. This work describes the basic elements of the proposed lidar system and presents two potential ranging mechanisms, along with their experimental results demonstrating the real-time performance of our first prototype.”

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Publication: Journal of Optics
Issue/Year: Journal of Optics, Volume 24; Number 3; Pages 035701; 2022
DOI: 10.1088/2040-8986/ac4870