Integrated photonic devices and artificial intelligence have presented a significant opportunity for the advancement of optical computing in practical applications. Optical computing technology is a unique computing system based on optical devices and computing functions, which significantly differs from the traditional electronic computing technology. On the other hand, optical computing technology offers the advantages such as fast speed, low energy consumption, and high parallelism. Yet there are still challenges such as device integration and portability. In the burgeoning development of micro-nano optics technology, especially the deeply ingrained concept of metasurface technique, it provides an advanced platform for optical computing applications, including edge detection, image or motion recognition, logic computation, and on-chip optical computing. With the aim of providing a comprehensive introduction and perspective for optical computing metasurface applications, we review the recent research advances of optical computing, from nanostructure and computing methods to practical applications. In this work, we review the challenges and analysis of optical computing metasurfaces in engineering field and look forward to the future development trends of optical computing.
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http://dx.doi.org/10.1515/nanoph-2023-0871 | DOI Listing |
Sci Rep
December 2024
Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, 61186, Republic of Korea.
Polarization-sensitive optical coherence tomography (PS-OCT) measures the polarization state of backscattered light from tissues and provides valuable insights into the birefringence properties of biological tissues. Contrastive unpaired translation (CUT) was used in this study to generate a synthetic PS-OCT image from a single OCT image. The challenges related to extensive data requirements relying on labeled datasets using only pixel-wise correlations that make it difficult to efficiently regenerate the periodic patterns observed in PS-OCT images were addressed.
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December 2024
Department of Electronics, Carleton University, Ottawa, ON, K1S 5B6, Canada.
In this paper, we propose a novel structure of anisotropic graphene-based hyperbolic metamaterial (AGHMM) sandwiched as a defect between two one-dimensional photonic crystals (PCs) in the terahertz (THz) region. The proposed structure is numerically simulated and analyzed using the transfer matrix method, effective medium theory and three-dimensional finite-difference time-domain. The defect layer of AGHMM consists of graphene sheets separated by subwavelength dielectric spacers.
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December 2024
Engineering Product Development, Singapore University of Technology and Design, Singapore, 487372, Singapore.
Spatially selective imaging (SSI) involves sampling a group of pixels from different positions on an encoded object to display a decoded image. Here, SSI is achieved by using off-axis cylindrical Fresnel lens arrays to decode multiple images from an encoded print of structural color pixels. Each image is optically retrieved by separately placing different "keys" (arrays of lenses in different pseudorandom configurations) over the same encoded print, and then each image is digitally reconstructed for visualization.
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December 2024
College of Computer Science, Chengdu University, Chengdu, 610106, China.
This study offers a comprehensive analysis of the Perturbed Schrödinger -Hirota Equation (PSHE), crucial for understanding soliton dynamics in modern optical communication systems. We extended the traditional Nonlinear Schrödinger Equation (NLSE) to include higher-order nonlinearities and spatiotemporal dispersion, capturing the complexities of light pulse propagation. Employing the modified auxiliary equation method and Adomian Decomposition Method (ADM), we derived a spectrum of exact traveling wave solutions, encompassing exponential, rational, trigonometric, and hyperbolic functions.
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December 2024
Neurology, Icahn School of Medicine at Mount Sinai, New York, USA.
We used machine learning to investigate the residual visual field (VF) deficits and macula retinal ganglion cell (RGC) thickness loss patterns in recovered optic neuritis (ON). We applied archetypal analysis (AA) to 377 same-day pairings of 10-2 VF and optical coherence tomography (OCT) macula images from 93 ON eyes and 70 normal fellow eyes ≥ 90 days after acute ON. We correlated archetype (AT) weights (total weight = 100%) of VFs and total retinal thickness (TRT), inner retinal thickness (IRT), and macular ganglion cell-inner plexiform layer (GCIPL) thickness.
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