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Photonics
Volume 12
Issue 2
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Photonics, Volume 12, Issue 2 (February 2025) – 79 articles

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14 pages, 4858 KiB  
Article
Synthesis and Characterization of Smartphone-Readable Luminescent Lanthanum Borates Doped and Co-Doped with Eu and Dy
by Katya Hristova, Irena P. Kostova, Tinko A. Eftimov, Georgi Patronov and Slava Tsoneva
Photonics 2025, 12(2), 171; https://doi.org/10.3390/photonics12020171 - 19 Feb 2025
Viewed by 322
Abstract
Despite notable advancements in the development of borate materials, improving their luminescent efficiency remains an important focus in materials research. The synthesis of lanthanum borates (LaBO3), doped and co-doped with europium (Eu3⁺) and dysprosium (Dy3⁺), by the [...] Read more.
Despite notable advancements in the development of borate materials, improving their luminescent efficiency remains an important focus in materials research. The synthesis of lanthanum borates (LaBO3), doped and co-doped with europium (Eu3⁺) and dysprosium (Dy3⁺), by the solid-state method, has demonstrated significant potential to address this challenge due to their unique optical properties. These materials facilitate efficient energy transfer from UV-excited host crystals to trivalent rare-earth activators, resulting in stable and high-intensity luminescence. To better understand their structural and vibrational characteristics, Fourier transform infrared (FTIR) spectroscopy and Raman spectroscopy were employed to identify functional groups and molecular vibrations in the synthesized materials. Additionally, X-ray diffraction (XRD) analysis was conducted to determine the crystalline structure and phase composition of the samples. All observed transitions of Eu3⁺ and Dy3⁺ in the excitation and emission spectra were systematically analyzed and identified, providing a comprehensive understanding of their behavior. Although smartphone cameras exhibit non-uniform spectral responses, their integration into this study highlights distinct advantages, including contactless interrogation, effective UV excitation suppression, and real-time spectral analysis. These capabilities enable practical and portable fluorescence sensing solutions for applications in healthcare, environmental monitoring, and food safety. By combining advanced photonic materials with accessible smartphone technology, this work demonstrates a novel approach for developing low-cost, scalable, and innovative sensing platforms that address modern technological demands. Full article
(This article belongs to the Section Optoelectronics and Optical Materials)
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<p>Experimental set-up: left is the basic arrangements for the measurement of the 3D excitation–emission spectra of the samples using a standard optical fiber spectrometer; right is a side view of the arrangement from a smartphone camera equipped with a sheet transmission diffraction grating (1000 L/mm) to observe the spectrum.</p> Full article ">Figure 2
<p>XRD patterns of LaBO<sub>3</sub> doped with Eu and Dy and software-generated crystal structure model of LaBO<sub>3</sub>.</p> Full article ">Figure 3
<p>FTIR spectra of samples: LaBO<sub>3</sub>:Eu<sup>3+</sup> (S1), LaBO<sub>3</sub>:Dy<sup>3+</sup> (S2), and LaBO<sub>3</sub>:Eu<sup>3+</sup>:Dy<sup>3+</sup> (S3).</p> Full article ">Figure 4
<p>Raman analysis of sample S3.</p> Full article ">Figure 5
<p>Raman analysis of samples S1–S3.</p> Full article ">Figure 6
<p>Graphic representation of the emission intensity at 591 nm, 615 nm, 683 nm, and 708 nm vs. excitation wavelength of 290 nm, 350, 360, 390, 420, 430, 450, and 465 nm for lanthanum borate doped with Eu.</p> Full article ">Figure 7
<p>Emission spectra of co-doped LaBO<sub>3</sub> at λ<sub>exc</sub> = 290 nm and 350 nm.</p> Full article ">Figure 8
<p>Topographic and 3D representation of excitation at 290 nm and 396 nm and emission at 589 nm and 615 nm for sample LaBO<sub>3</sub>:Eu<sup>3+</sup>:Dy<sup>3+</sup>, measured by an Ocean Optics spectrometer.</p> Full article ">Figure 9
<p>Topographic and 3D representation of excitation at 290 nm and 396 nm and emission at 589 nm and 615 nm for sample LaBO<sub>3</sub>:Eu<sup>3+</sup>:Dy<sup>3+</sup>, measured by mobile phone.</p> Full article ">Figure 10
<p>(<b>a</b>) Comparative graph of samples S1 and S3 for ~615 nm emission at 396 nm excitation, and for sample S2 for 569 nm emission at excitation at 391 nm; (<b>b</b>) comparative graph of samples S1 and S3 at ~591 nm emission at 290 nm and 396 nm excitation, and S2 at 569 nm emission at 393 nm excitation.</p> Full article ">Scheme 1
<p>Representation of the synthesis of luminescent materials.</p> Full article ">
12 pages, 5774 KiB  
Article
Macroscopic Fourier Ptychographic Imaging Based on Deep Learning
by Junyuan Liu, Wei Sun, Fangxun Wu, Haoming Shan and Xiangsheng Xie
Photonics 2025, 12(2), 170; https://doi.org/10.3390/photonics12020170 - 19 Feb 2025
Viewed by 221
Abstract
Fourier Ptychography (FP) is a powerful computational imaging technique that enables high-resolution, wide-field imaging by synthesizing apertures and leveraging coherent diffraction. However, the application of FP in long-distance imaging has been limited due to challenges such as noise and optical aberrations. This study [...] Read more.
Fourier Ptychography (FP) is a powerful computational imaging technique that enables high-resolution, wide-field imaging by synthesizing apertures and leveraging coherent diffraction. However, the application of FP in long-distance imaging has been limited due to challenges such as noise and optical aberrations. This study introduces deep learning methods following macroscopic FP to further enhance image quality. Specifically, we employ super-resolution convolutional neural networks and very deep super-resolution, incorporating residual learning and residual neural network architectures to optimize network performance. These techniques significantly improve the resolution and clarity of FP images. Experiments with real-world film samples demonstrate the effectiveness of the proposed methods in practical applications. This research highlights the potential of deep learning to advance computational imaging techniques like FP, paving the way for improved long-distance imaging capabilities. Full article
(This article belongs to the Special Issue Optical Imaging Innovations and Applications)
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<p>Schematic of macroscopic FP.</p> Full article ">Figure 2
<p>Schematic of the reconstruction process of macroscopic FP.</p> Full article ">Figure 3
<p>(<b>a</b>) Original-resolution target with smallest line pairs of 1 pixel. (<b>b</b>) Imaging with a single aperture with the optical resolution limit of 9 pixels (indicated in red box). (<b>c</b>) FP with 7 × 7 scanning aperture with a resolution limit of 3 pixels (indicated in red box).</p> Full article ">Figure 4
<p>(<b>a</b>) The SRCNN process of constructing training pairs. (<b>b</b>) SRCNN structure.</p> Full article ">Figure 5
<p>(<b>a</b>) Process of residual learning method. (<b>b</b>) VDSR structure.</p> Full article ">Figure 6
<p>SRCNN-residual network structure.</p> Full article ">Figure 7
<p>Residual learning framework. Rectified Linear Unit (ReLU) is an activation function.</p> Full article ">Figure 8
<p>VDSR-ResNet learning framework.</p> Full article ">Figure 9
<p>Simulation comparison of the image quality with four deep learning networks for the FP image.</p> Full article ">Figure 10
<p>Experimental setup for the FP imaging.</p> Full article ">Figure 11
<p>Experimental result: Recovering a USAF resolution chart with 1.75 SAR. (<b>a</b>) Ground truth, (<b>b</b>) Center input and (<b>c</b>) recovered image.</p> Full article ">Figure 12
<p>Deep learning framework to process the image of the USAF resolution chart.</p> Full article ">Figure 13
<p>Deep learning framework to process film sample results.</p> Full article ">
10 pages, 1797 KiB  
Article
Laser Power Modulation of Fiber Coated with Multilayer-Graphene Based on Lithium Intercalation Method
by Zhenyu Fang, Ganying Zeng, Yijie Li, Zixuan Wang, Liantuan Xiao, Suotang Jia and Chengbing Qin
Photonics 2025, 12(2), 169; https://doi.org/10.3390/photonics12020169 - 19 Feb 2025
Viewed by 271
Abstract
Dynamic manipulation of light in optical fibers has attracted extensive interest due to its compatibility with various fiber-optic systems. The integration of two-dimensional (2D) materials on the surface of optical fibers is an effective method to manipulate light beams. However, it is still [...] Read more.
Dynamic manipulation of light in optical fibers has attracted extensive interest due to its compatibility with various fiber-optic systems. The integration of two-dimensional (2D) materials on the surface of optical fibers is an effective method to manipulate light beams. However, it is still a huge challenge to acquire dynamic modulation for light signals in fiber. In this work, we develop electrically manipulable in-line multilayer graphene (MLG) devices by integrating a graphene-based lithium-ion (Li-ion) battery on a side-polished fiber. Through charge and discharge processes with a current of 400 µA, the output power of a 1550 nm laser can be cyclically tuned in the range of ~120 and ~240 µW with a response time of about 1.8 min. After 100 cycles of testing, the modulation power of the laser system remains nearly unchanged, exhibiting good stability. The optical modification of MLG is due to the shift of Fermi energy (Ef), which results from charge transfer between Li and graphene layers. Therefore, the light in the fiber can be modulated due to the change in the optical absorbance of MLG. Our findings imply potential value in fabricating fiber-intergraded 2D intercalation materials with high tunability. Full article
(This article belongs to the Special Issue Thermal Radiation and Micro-/Nanophotonics)
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<p>Device structure and working principle. (<b>a</b>) Schematic diagram of the device structure consisting of anode MLG film, PE separator soaked in electrolyte, and cathode Li-NMC. Two pieces of Al foil are the current collector for cathode and anode materials. (<b>b</b>) Demonstration of Li-ions and electrons behavior during charge and discharge processes. (<b>c</b>) Schematic diagram of the Ef of MLG before and after Li intercalation. (<b>d</b>) Electrochemical potential versus lithiation time of MLG during charge process. (<b>e</b>) Detail of voltage profile versus time corresponding to the curve in the red box of (<b>d</b>). (<b>f</b>) Optical images of MLG, LiC<sub>18</sub>, LiC<sub>12</sub>, and LiC<sub>6</sub>, respectively.</p> Full article ">Figure 2
<p>Characterization of MLG and Li-intercalated MLG. (<b>a</b>,<b>b</b>) Raman spectra of MLG and Li-GIC at different stages. (<b>c</b>) XRD test of MLG before (black line) and after intercalation (red line). (<b>d</b>) Four-probe I versus V curves for MLG before (black) and after intercalation (red line). (<b>e</b>) The absorbance spectra as a function of wavelength for MLG at different electrochemical potentials. (<b>f</b>) The absorbance at 1550 nm wavelength as a function of electrochemical potential versus Li/Li<sup>+</sup>.</p> Full article ">Figure 3
<p>(<b>a</b>,<b>b</b>) Fiber laser system configuration includes a graphene-based Li-ion battery. (<b>c</b>) The output power of the laser corresponds to intercalation (red line) and no intercalation (black line) during 100 charge and discharge cycles. The current is 400 µA during the charge and discharge process. (<b>d</b>) Typical voltage profile of MLG during the first 25th charge and discharge cycles, with a constant current of 400 µA. The other voltage profile of MLG during the first 25th to 100th charge and discharge cycles is shown in <a href="#app1-photonics-12-00169" class="html-app">Figure S4</a>.</p> Full article ">Figure 4
<p>(<b>a</b>) The output power of a laser during charge (orange area) and discharge (green area) for the 10th, 20th, 30th, 40th, 50th, 60th, 70th, 80th, 90th, and 100th cycles, respectively. The current is 400 µA during the charge and discharge process. (<b>b</b>) The difference of output power vs. the number of cycles. The difference of output power between 3.6 V and 3.8 V is extracted from (<b>a</b>).</p> Full article ">
12 pages, 76138 KiB  
Article
Structured Light Field Recovery from Dynamic Scattering Media
by Shiwen Zhou, Guangcui Mo, Zepei Zeng, Yanwen Hu and Shenhe Fu
Photonics 2025, 12(2), 168; https://doi.org/10.3390/photonics12020168 - 19 Feb 2025
Viewed by 182
Abstract
Performing light field recovery from diffusing wave is difficult owing to its complex and randomized light behaviors imposed by scatters. The problem becomes even more challenging when a time-varying scattering medium is involved, because, the scattered light changes in space and time. Here [...] Read more.
Performing light field recovery from diffusing wave is difficult owing to its complex and randomized light behaviors imposed by scatters. The problem becomes even more challenging when a time-varying scattering medium is involved, because, the scattered light changes in space and time. Here we report theoretically and experimentally an approach to structured field recovery behind a dynamic scattering medium, both in the near-field and the far-field diffraction regimes. We exploit the temporal irregular scattering behaviors of the dynamic scatter to overcome light field distortions, without any prior knowledge or wavefront control technique. Of particular interest is that the technique can work with a fast response rate of the scattering change in the order of microsecond level, which is inaccessible with previous techniques. Furthermore, we demonstrate the possibility for recovering a higher-order vector vortex light field from a dynamic diffuser, which was not addressed before. This work shows a significant advance toward light field recovery behind the dynamic scatters and may find intriguing applications. Full article
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<p>Simulations for structured light field recovery in the Fresnel regime with scattering strength setting as <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.7</mn> </mrow> </semantics></math>. The object field is given by periodic fringes with different carrier wave numbers: (<b>a</b>–<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mi>x</mi> </msub> <mo>=</mo> <mn>2</mn> </mrow> </semantics></math> mm<sup>−1</sup>, <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mi>y</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, and (<b>d</b>–<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mi>x</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mi>y</mi> </msub> <mo>=</mo> <mn>2</mn> </mrow> </semantics></math> mm<sup>−1</sup>. (<b>a</b>,<b>d</b>) Original light fields (<math display="inline"><semantics> <mrow> <mi>z</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>); (<b>b</b>,<b>e</b>) instant light speckles (<math display="inline"><semantics> <mrow> <mi>z</mi> <mo>=</mo> <mn>250</mn> </mrow> </semantics></math> mm); and (<b>c</b>,<b>f</b>) recovered light fields (<math display="inline"><semantics> <mrow> <mi>z</mi> <mo>=</mo> <mn>250</mn> </mrow> </semantics></math> mm). (<b>g</b>) Three uncorrelated profiles of the speckles generated from (<b>b</b>) at different record time. Panels (<b>a</b>–<b>f</b>) share the same scale (scale bar, 5 mm).</p> Full article ">Figure 2
<p>Experiments for structured field recovery. (<b>a</b>) Experimental setup. LP: linear polarizer; OB: object; DSM: dynamic scattering medium. (<b>b</b>–<b>g</b>) Experimental results for fringe recovery. A double slit (slit width is 1 mm) was utilized to produce periodic fringes (<b>b</b>). (<b>d</b>) shows an instant speckle of (<b>b</b>) generated by a refreshing spatial light modulator (SLM) imprinted with random phase mask (<b>c</b>). (<b>e</b>) shows the restored intensity fringes of (<b>b</b>) using the SLM. (<b>f</b>) a light speckle of (<b>b</b>) generated by a rotatory frosted glass; while (<b>g</b>) shows its recovered fringes of (<b>b</b>). (<b>b</b>,<b>d</b>–<b>g</b>) share the same scale. Scale bar, 1 mm.</p> Full article ">Figure 3
<p>Experimental results for object wave recovery in the millisecond scale. (<b>a</b>) An original object showing a circular aperture. (<b>b</b>) An instant speckle of (<b>a</b>). (<b>c</b>) The recovered object of (<b>a</b>). (<b>d</b>–<b>f</b>) The reconstructed objects of other apertures having different geometric shapes: (<b>d</b>) hexagon, (<b>e</b>) triangle, and (<b>f</b>) quadrilateral. All the panels share the same scale. Scale bar, 0.3 mm.</p> Full article ">Figure 4
<p>Experiments for object recovery in the microsecond level. (<b>a</b>,<b>d</b>) The original objects of a circular ring (<b>a</b>) and a triangle slit (<b>d</b>). (<b>b</b>,<b>e</b>) The instant speckles of (<b>a</b>,<b>d</b>). (<b>c</b>,<b>f</b>) The restored object patterns of (<b>a</b>,<b>d</b>). All panels share the same scale. Scale bar, 1 mm.</p> Full article ">Figure 5
<p>Simulated results for vortex phase recovery with topology of <math display="inline"><semantics> <mrow> <mi>l</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>. (<b>a</b>) An intensity speckle recorded at distance of <math display="inline"><semantics> <mrow> <mi>z</mi> <mo>=</mo> <mn>25</mn> </mrow> </semantics></math> mm, generated by a dynamic scatter with scattering strength of <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.8</mn> </mrow> </semantics></math>. (<b>b</b>) The recovery of LG intensity distributions after processing over 500 diffractive frames. (<b>c</b>) Phase distribution of (<b>a</b>). (<b>d</b>–<b>f</b>) Phase profiles for averaged field with iteration number: (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>50</mn> </mrow> </semantics></math>, (<b>e</b>) <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>, and (<b>f</b>) <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>500</mn> </mrow> </semantics></math>. Scalar bar for (<b>a</b>,<b>b</b>) is 1 mm, while scalar bar for (<b>c</b>–<b>f</b>) is 0.4 mm. The colorbar ranging from <math display="inline"><semantics> <mrow> <mo>−</mo> <mi>π</mi> </mrow> </semantics></math> (low) to <math display="inline"><semantics> <mi>π</mi> </semantics></math> (high) is utilized for panels (<b>c</b>–<b>f</b>).</p> Full article ">Figure 6
<p>Spatial distributions of typical vector vortex states, with three different value of <math display="inline"><semantics> <mi>α</mi> </semantics></math>: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>4</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics></math>. The colorbar is ranging from <math display="inline"><semantics> <mrow> <mo>−</mo> <mi>π</mi> </mrow> </semantics></math> (low) to <math display="inline"><semantics> <mi>π</mi> </semantics></math> (high).</p> Full article ">Figure 7
<p>Simulated results for recovering the vector vortex states with two encoded phase values: (<b>a</b>–<b>c</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, (<b>d</b>–<b>f</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics></math>. (<b>a</b>,<b>d</b>) One of the intensity speckles of vector vortex beams recorded at <math display="inline"><semantics> <mrow> <mi>z</mi> <mo>=</mo> <mn>25</mn> </mrow> </semantics></math> mm. The scattering strength of the scatter is set as <math display="inline"><semantics> <mrow> <mi>ε</mi> <mo>=</mo> <mn>0.8</mn> </mrow> </semantics></math>. (<b>b</b>,<b>e</b>) The recovered structured states after processing over 500 diffractive frames. (<b>c</b>,<b>f</b>) show their <span class="html-italic">x</span>-component of (<b>b</b>,<b>e</b>), which match well with the encrypted phase values: <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics></math>. All panels share the same scale. Scale bar, 1 mm. The colorbar is ranging from <math display="inline"><semantics> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </semantics></math> (low) to 1 (high).</p> Full article ">Figure 8
<p>Experiments for vector vortex state recoveries with three encoded phase values: (<b>a</b>–<b>c</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, (<b>d</b>–<b>f</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>3</mn> <mi>π</mi> <mo>/</mo> <mn>4</mn> </mrow> </semantics></math>, and (<b>g</b>–<b>i</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics></math>. (<b>a</b>,<b>d</b>,<b>g</b>) The original well-defined structured states; (<b>b</b>,<b>e</b>,<b>h</b>) one of their <span class="html-italic">x</span>-component speckles; and (<b>c</b>,<b>f</b>,<b>i</b>) the retrieved states, which display their <span class="html-italic">x</span>-components having different phase values: (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, (<b>f</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>3</mn> <mi>π</mi> <mo>/</mo> <mn>4</mn> </mrow> </semantics></math>, and (<b>i</b>) <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mi>π</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics></math>. Panels in second and third columns share the same scale. Scale bar, 0.5 mm.</p> Full article ">
10 pages, 5162 KiB  
Article
Portable Filter-Free Lens-Free Incoherent Digital Holography System
by Tatsuki Tahara
Photonics 2025, 12(2), 167; https://doi.org/10.3390/photonics12020167 - 19 Feb 2025
Viewed by 193
Abstract
A portable incoherent digital holography system without a polarization filter or a refractive lens was developed. Phase-shifted self-interference incoherent holograms of light diffracted from an object were generated without attenuation due to a polarization filter using two polarization-sensitive phase-only spatial light modulators (TPP-SLMs). [...] Read more.
A portable incoherent digital holography system without a polarization filter or a refractive lens was developed. Phase-shifted self-interference incoherent holograms of light diffracted from an object were generated without attenuation due to a polarization filter using two polarization-sensitive phase-only spatial light modulators (TPP-SLMs). The number of optical elements in filter-free lens-free incoherent digital holography was reduced to make the system compact and portable. Experiments were conducted using the developed digital holography system set on a tripod stand and objects illuminated by a light-emitting diode. Full article
(This article belongs to the Special Issue Optical Imaging Innovations and Applications)
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<p>Schematic of the optical setup of the developed IDH system.</p> Full article ">Figure 2
<p>Photographs of the developed IDH system. (<b>a</b>) Inside of the body containing the developed IDH optical setup, and (<b>b</b>) the developed IDH system set on a tripod stand.</p> Full article ">Figure 3
<p>Experimental results for IDH recording of an aperture. (<b>a</b>) Phase-shifted holograms recorded using an LED. (<b>b</b>) Amplitude and (<b>c</b>) phase distributions on the image sensor plane. (<b>d</b>) Reconstructed image after numerical refocusing. The numerical propagation distance <span class="html-italic">f<sub>c</sub></span> was 460 mm.</p> Full article ">Figure 4
<p>Experimental results for a transmissive object. (<b>a</b>) Recorded phase-shifted spatially incoherent holograms. Reconstructed (<b>b</b>) intensity and (<b>c</b>) phase distributions after numerical refocusing. The numerical propagation distance <span class="html-italic">f<sub>c</sub></span> was 960 mm.</p> Full article ">Figure 5
<p>Experimental results for a reflective object. (<b>a</b>) Recorded phase-shifted spatially incoherent holograms. (<b>b</b>) Amplitude and (<b>c</b>) phase distributions on the image sensor plane. (<b>d</b>) Amplitude and (<b>e</b>) phase distributions on the object image plane, obtained by four-step PSI and calculated by numerical refocusing. (<b>f</b>) Amplitude and (<b>g</b>) phase distributions, obtained by three-step PSI and calculated by numerical refocusing. The numerical propagation distance <span class="html-italic">f<sub>c</sub></span> was 1110 mm.</p> Full article ">
14 pages, 714 KiB  
Article
Design and Analysis of Enhanced IM/DD System with Nonorthogonal Code Shift Keying and Parallel Transmission
by Nobuyoshi Komuro and Hiromasa Habuchi
Photonics 2025, 12(2), 166; https://doi.org/10.3390/photonics12020166 - 19 Feb 2025
Viewed by 171
Abstract
Providing Optical Wireless Communications (OWCs) is desirable for high data transmission efficiency. Intensity Modulation and Direct Detection (IM/DD) is widely adopted for its simplicity and practicality. Among various modulation schemes, Code Shift Keying (CSK) has demonstrated superior transmission efficiency compared to On-Off Keying [...] Read more.
Providing Optical Wireless Communications (OWCs) is desirable for high data transmission efficiency. Intensity Modulation and Direct Detection (IM/DD) is widely adopted for its simplicity and practicality. Among various modulation schemes, Code Shift Keying (CSK) has demonstrated superior transmission efficiency compared to On-Off Keying (OOK) and Pulse Position Modulation (PPM). Prior research has shown that CSK performance can be further enhanced through parallel transmission and code concatenation techniques. However, the direct application of concatenated CSK to parallel transmission reduces the number of available code combinations as the concatenation level increases, potentially lowering modulation efficiency. This study proposes an advanced transmission scheme that integrates parallel transmission with a multi-level intensity adjustment mechanism. The proposed method preserves a high number of distinguishable transmission symbols, thereby achieving higher data transmission rates. Analytical derivations for transmission efficiency are provided for single-user scenarios, and numerical simulations validate the effectiveness of the proposed system. The key contributions of this work include mitigating symbol reduction in nonorthogonal CSK with parallel transmission and adjusting the multi-level intensity to enhance overall system performance. The results confirm that the proposed scheme significantly improves the efficiency and scalability of nonorthogonal CSK in OWC applications. Full article
(This article belongs to the Special Issue Advanced Technologies in Optical Wireless Communications)
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<p>Proposed system architecture.</p> Full article ">Figure 2
<p>Example of transmitted signal structure.</p> Full article ">Figure 3
<p>Receiver workflow.</p> Full article ">Figure 4
<p>Simulation diagram.</p> Full article ">Figure 5
<p>Data transmission efficiency as a function of the parallel level.</p> Full article ">Figure 6
<p>Data transmission efficiency as a function of the transmit laser power per bit.</p> Full article ">Figure 7
<p>Data transmission efficiency as a function of the APD effective ionization ratio, <math display="inline"><semantics> <msub> <mi>k</mi> <mrow> <mi>e</mi> <mi>f</mi> <mi>f</mi> </mrow> </msub> </semantics></math>.</p> Full article ">Figure 8
<p>Comparison of data transmission efficiency as the proposed and conventional systems.</p> Full article ">Figure 9
<p>Data transmission efficiency as a function of the frame length.</p> Full article ">
11 pages, 495 KiB  
Article
Time-Averaged Energy Flow and Momentum of Electromagnetic Waves in Homogeneous Isotropic Linear Media
by Quanzhi Kougong and Jiangwei Chen
Photonics 2025, 12(2), 165; https://doi.org/10.3390/photonics12020165 - 19 Feb 2025
Viewed by 180
Abstract
There exist multiple different even non-equivalent expressions describing characteristics of electromagnetic wave energy flow and momentum in media, which makes the issue confusing. For simplicity (without loss of generality), we shall consider a case where a harmonic homogeneous plane wave (HHPW) travels in [...] Read more.
There exist multiple different even non-equivalent expressions describing characteristics of electromagnetic wave energy flow and momentum in media, which makes the issue confusing. For simplicity (without loss of generality), we shall consider a case where a harmonic homogeneous plane wave (HHPW) travels in a homogeneous isotropic linear medium (HILM); thus, both time-dependent Poynting’s vector S⃑(t) and time-dependent momentum density G⃑(t) are rigorously derived from continuity equations. Then, referring to recent studies of stored and dissipated energies of electromagnetic waves in lossy media, time-averaged Poynting’s vector <S⃑> and time-averaged momentum density <G⃑> are obtained according to the time dependence of the terms arising in the expressions of S⃑(t) and G⃑(t), respectively. On this basis, a new way is proposed to determine the direction relation between <S⃑> and <G⃑> of HHPWs in an HILM, and it is demonstrated that, in an HILM, the propagation direction of <S⃑> is always consistent with that of <G⃑>, which may be applied to explain why the predicted reversal of electromagnetic wave momentum in a left-handed material has not been observed up to now. This work may be helpful to further discuss, and even eliminate, the confusion arising in related issues, and deepen the understanding of the energy flow and momentum of electromagnetic waves in media. Full article
(This article belongs to the Section Optoelectronics and Optical Materials)
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<p>Sketch of an HHPW traveling along the <span class="html-italic">+z</span> direction in an HILM.</p> Full article ">
21 pages, 2027 KiB  
Review
Research Progress and Applications of Single-Pixel Imaging Technology
by Jincai Hu, Qichang An, Wenjie Wang, Tong Li, Lin Ma, Shufei Yi and Liang Wang
Photonics 2025, 12(2), 164; https://doi.org/10.3390/photonics12020164 - 18 Feb 2025
Viewed by 191
Abstract
Single-pixel imaging is a computational optical imaging technique that uses a single-pixel detector to obtain scene information and reconstruct the image. Compared with traditional imaging techniques, single-pixel imaging has the advantages of high sensitivity and a wide dynamic range, etc., which make it [...] Read more.
Single-pixel imaging is a computational optical imaging technique that uses a single-pixel detector to obtain scene information and reconstruct the image. Compared with traditional imaging techniques, single-pixel imaging has the advantages of high sensitivity and a wide dynamic range, etc., which make it have broad application prospects in special frequency band imaging and scattering media imaging. This paper mainly introduces the history of development and the characteristics of the single-pixel detector, focuses on the typical applications of single-pixel imaging in coded aperture, transverse scanning, and longitudinal scanning systems, and gives an account of the application of deep learning technology in single-pixel imaging. At the end of this paper, the development of single-pixel imaging is summarized and future trends forecasted. Full article
(This article belongs to the Special Issue Challenges and Future Directions in Adaptive Optics Technology)
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<p>Pre-modulation SPI (<b>right</b>) and post-modulation SPI (<b>left</b>).</p> Full article ">Figure 2
<p>Schematic of a coded aperture system.</p> Full article ">Figure 3
<p>Schematic of ghost imaging using rotating ground glass.</p> Full article ">Figure 4
<p>Schematic of OCT system: TD-OCT (<b>left</b>) and FD-OCT (<b>right</b>).</p> Full article ">Figure 5
<p>Basic steps of point cloud processing.</p> Full article ">Figure 6
<p>Schematic of a Michelson interferometer.</p> Full article ">
13 pages, 5267 KiB  
Communication
Propagation Properties of Laguerre–Gaussian Beams with Three Variable Coefficient Modulations in the Fractional Schrödinger Equation
by Xinru Hao, Yong Liang, Min Zou, Bin Zhong and Chao Tan
Photonics 2025, 12(2), 163; https://doi.org/10.3390/photonics12020163 - 18 Feb 2025
Viewed by 238
Abstract
This article investigates the transmission characteristics of Laguerre–Gaussian (LG) beams under cosine modulation, power function modulation and linear modulation based on the variable coefficient fractional Schrödinger equation (FSE), respectively. In the absence of modulation, the LG beam undergoes diffraction-induced expansion as the transmission [...] Read more.
This article investigates the transmission characteristics of Laguerre–Gaussian (LG) beams under cosine modulation, power function modulation and linear modulation based on the variable coefficient fractional Schrödinger equation (FSE), respectively. In the absence of modulation, the LG beam undergoes diffraction-induced expansion as the transmission distance increases, with the degree of spreading increasing with a rising Lévy index. Under the cosine modulation, the evolution of the beam exhibits a periodic inversion, where the higher modulation frequency leads to a shorter oscillation period. The oscillation amplitude enlarges with a higher Lévy index and lower modulation frequency. When taking a power function modulation into account, the beam gradually evolves into a stable structure over propagation, with its width broadening with a growing Lévy index and modulation coefficient. In a linear modulation, the propagation of the LG beam forms a “trumpet-like” structure due to an accelerated diffraction effect. Notably, the transmission of the beam is not affected by the radial and azimuthal indices, but its ring number and phase singularity are changed correspondingly. The beam behaves in a similar evolutionary law under different modulations when the Lévy index is below 1. These findings offer valuable insights for applications in optical manipulation and communication. Full article
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<p>(<b>a0</b>–<b>c0</b>) Evolution of LG beams for different Lévy indices <math display="inline"><semantics> <mi>α</mi> </semantics></math>, (<b>a1</b>–<b>c1</b>) intensity distribution at <span class="html-italic">z</span> = 7 in the <math display="inline"><semantics> <mrow> <mi>x</mi> <mtext>-</mtext> <mi>y</mi> </mrow> </semantics></math> plane, (<b>d</b>) envelope corresponding to (<b>a0</b>–<b>c0</b>).</p> Full article ">Figure 2
<p>(<b>a0</b>–<b>c0</b>) Evolution of LG beams for different Lévy indices <math display="inline"><semantics> <mi>α</mi> </semantics></math> under cosine modulation, <math display="inline"><semantics> <mrow> <mi>Ω</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>. (<b>a1</b>–<b>a3</b>,<b>b1</b>–<b>b3</b>,<b>c1</b>–<b>c3</b>) The corresponding intensity distribution to (<b>a0</b>–<b>c0</b>). (<b>a4</b>–<b>a6</b>,<b>b4</b>–<b>b6</b>,<b>c4</b>–<b>c6</b>) The corresponding phase to (<b>a0</b>–<b>c0</b>).</p> Full article ">Figure 3
<p>(<b>a0</b>–<b>c0</b>) Evolution of LG beams for different modulation frequencies <math display="inline"><semantics> <mi>Ω</mi> </semantics></math> (<math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>). (<b>a1</b>–<b>c1</b>) The corresponding three-dimensional isosurface plots to (<b>a0</b>–<b>c0</b>). (<b>d</b>) The beam width and (<b>e</b>) the envelope vary with transmission distance <span class="html-italic">z</span>, respectively.</p> Full article ">Figure 4
<p>(<b>a0</b>–<b>c0</b>) Evolution of LG beams for different radial and azimuthal indices, <math display="inline"><semantics> <mrow> <mi>Ω</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>. (<b>a1</b>–<b>c3</b>) The corresponding intensity and phase distribution to (<b>a0</b>–<b>c0</b>).</p> Full article ">Figure 5
<p>(<b>a0</b>–<b>c0</b>) Evolution of LG beams for different Lévy indices <math display="inline"><semantics> <mi>α</mi> </semantics></math> under power function modulation, <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>. (<b>a1</b>–<b>c1</b>) Intensity distribution at z = 7 in <math display="inline"><semantics> <mrow> <mi>x</mi> <mtext>-</mtext> <mi>y</mi> </mrow> </semantics></math> plane. (<b>a2</b>–<b>c2</b>) The corresponding three-dimensional isosurface plots to (<b>a0</b>–<b>c0</b>). (<b>d0</b>) The beam width and (<b>d1</b>) the envelope vary with transmission distance <span class="html-italic">z</span>, respectively.</p> Full article ">Figure 6
<p>(<b>a0</b>–<b>c0</b>) Evolution of LG beams for different modulation coefficients <math display="inline"><semantics> <mi>k</mi> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>. (<b>a1</b>–<b>c3</b>) The corresponding intensity and phase distribution to (<b>a0</b>–<b>c0</b>).</p> Full article ">Figure 7
<p>(<b>a0</b>–<b>c0</b>) Evolution of LG beams for different radial and azimuthal indices, <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>. (<b>a1</b>–<b>c3</b>) The corresponding intensity and phase distribution to (<b>a0</b>–<b>c0</b>).</p> Full article ">Figure 8
<p>(<b>a0</b>–<b>c0</b>) Evolution of LG beams for different Lévy indices <math display="inline"><semantics> <mi>α</mi> </semantics></math> under linear modulation. (<b>a1</b>–<b>c3</b>) The corresponding intensity and phase distribution to (<b>a0</b>–<b>c0</b>). (<b>d0</b>–<b>d2</b>) The corresponding three-dimensional isosurface plots to (<b>a0</b>–<b>c0</b>).</p> Full article ">Figure 9
<p>(<b>a0</b>–<b>c0</b>) Evolution of LG beams for different radial and azimuthal indices under the linear modulation when <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>. (<b>a1</b>–<b>a3</b>,<b>b1</b>–<b>b3</b>,<b>c1</b>–<b>c3</b>) The corresponding intensity distribution to (<b>a0</b>–<b>c0</b>). (<b>a4</b>–<b>a6</b>,<b>b4</b>–<b>b6</b>,<b>c4</b>–<b>c6</b>) The corresponding phase to (<b>a0</b>–<b>c0</b>).</p> Full article ">Figure 10
<p>(<b>a0</b>–<b>c2</b>) Evolution of LG beam for different Lévy indices <math display="inline"><semantics> <mi>α</mi> </semantics></math> under various modulations when <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>&lt;</mo> <mn>1</mn> </mrow> </semantics></math>. (<b>a3</b>–<b>c3</b>) The envelope varies with transmission distance <span class="html-italic">z</span>.</p> Full article ">
15 pages, 22455 KiB  
Article
Highly Efficient Cutting of Quartz Glass with Low Roughness and Minor Chipping Using Bessel Laser Beams
by Lei Xiong, Yuhang An, Ling Zhang, Cheng Tang, Tianci Zhang, Aibin Zuo and Wenyan Gao
Photonics 2025, 12(2), 162; https://doi.org/10.3390/photonics12020162 - 18 Feb 2025
Viewed by 284
Abstract
The conventional method of cutting quartz glass with a knife often leads to undesirable effects, such as chipping, debris generation, and an inconsistent cut quality. Additionally, implementing the current methods of laser ablation cutting and crack control cutting presents challenges in ensuring both [...] Read more.
The conventional method of cutting quartz glass with a knife often leads to undesirable effects, such as chipping, debris generation, and an inconsistent cut quality. Additionally, implementing the current methods of laser ablation cutting and crack control cutting presents challenges in ensuring both the quality of the cut and the efficiency of the process. Previous reports have documented a single direct cut of thin quartz glass, albeit at a thickness of only 200 μm. In this study, we utilized a pulse-width-tunable Gaussian beam, in combination with an axicon and a beam-reducing mirror, to generate a high-quality Bessel beam. This process endows the quartz glass with a nano-porous structure with a thickness of 1 mm, enabling high-quality cutting in a single pass. The effects of laser-cutting speed and pulse width on the cutting cross-section and cut surface were investigated. The results of the experiments show that using the optimal cutting speed and pulse width significantly improved cutting quality, reduced surface damage and sputtering, enabled the penetration of the modified cutting cross-section throughout the material, and decreased cutting cross-section roughness to 607 nm Ra. This technique holds promise for the laser-processing industry, enhancing both the quality and efficiency of cutting 1 mm thick quartz glass. Full article
(This article belongs to the Special Issue Advanced Lasers and Their Applications, 2nd Edition )
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<p>Schematic of Bessel beam generation.</p> Full article ">Figure 2
<p>Bessel beam simulation. (<b>a</b>) Diagram of the structure of the Bessel beam. (<b>b</b>) Radial distribution of light intensity. (<b>c</b>) Diagram of the relative illumination in the x-direction.</p> Full article ">Figure 3
<p>Schematic diagram of the experimental setup.</p> Full article ">Figure 4
<p>Optical microscope diagram of damage to the backside of quartz glass. Cutting speeds and pulse widths shown are as follows: (<b>a</b>) 5 mm/s, 3 ps; (<b>b</b>) 3 mm/s, 6 ps; and (<b>c</b>) 3 mm/s, 8 ps.</p> Full article ">Figure 5
<p>Optical microscope diagrams of quartz glass frontal damage. Cutting speeds and pulse widths shown are as follows: (<b>a</b>) 1 mm/s, 10 ps; (<b>b</b>) 4 mm/s, 10 ps.</p> Full article ">Figure 6
<p>Laser-scanning speed versus melt zone width and sputter zone width for three different backside morphology pulse widths: (<b>a</b>) 2 ps; (<b>b</b>) 6 ps; and (<b>c</b>) 10 ps.</p> Full article ">Figure 7
<p>Optical microscope images of quartz glass at a pulse width of 1 ps and a cutting speed of 3 mm/s, depicting (<b>a</b>) front view and (<b>b</b>) reverse view.</p> Full article ">Figure 8
<p>Depth of damage to quartz glass surface versus pulse width and cutting speed.</p> Full article ">Figure 9
<p>Scanning electron micrographs of quartz glass cutting cross-section. Cutting speeds and pulse widths shown are as follows: (<b>a</b>) 1 mm/s, 5 ps; (<b>b</b>) 5 mm/s, 5 ps.</p> Full article ">Figure 10
<p>High-magnification scanning electron microscope images of quartz glass cutting cross-section. Cutting speeds and pulse widths shown are as follows: (<b>a</b>) 1 mm/s, 5 ps; (<b>b</b>) 5 mm/s, 5 ps.</p> Full article ">Figure 11
<p>Cutting cross-section of quartz glass cut with optimum parameters. (<b>a</b>) Optical microscope image of the cutting cross-section. (<b>b</b>) Scanning electron microscope image of the cutting cross-section. (<b>c</b>) Roughness of the cutting cross-section.</p> Full article ">
11 pages, 2029 KiB  
Communication
Efficient Frequency-Domain Block Equalization for Mode-Division Multiplexing Systems
by Yifan Shen, Jianyong Zhang, Shuchao Mi, Guofang Fan and Muguang Wang
Photonics 2025, 12(2), 161; https://doi.org/10.3390/photonics12020161 - 17 Feb 2025
Viewed by 271
Abstract
In this paper, an adaptive frequency-domain block equalizer (FDBE) implementing the adaptive moment estimation (Adam) algorithm is proposed for mode-division multiplexing (MDM) optical fiber communication systems. By packing all frequency components into frequency-dependent blocks of a specified size B, we define an [...] Read more.
In this paper, an adaptive frequency-domain block equalizer (FDBE) implementing the adaptive moment estimation (Adam) algorithm is proposed for mode-division multiplexing (MDM) optical fiber communication systems. By packing all frequency components into frequency-dependent blocks of a specified size B, we define an adaptive equalization matrix to simultaneously compensate for multiple frequency components at each block, which is computed iteratively using the Adam, recursive least squares (RLS) and least mean squares (LMS) algorithms. Simulations show that the proposed FDBE using the Adam algorithm outperforms those using the LMS and RLS algorithms in terms of adaptation speed and symbol error rate (SER) performance. The FDBE using the Adam algorithm with B=1 has the fastest adaption time, requiring about ntr=100 and ntr=900 less training blocks than the RLS algorithm at the SER of 3.8×10−3 for the accumulated mode-dependent loss (MDL) of ξ=1 dB and ξ=5 dB, respectively. The Adam algorithm with B=16 and B=8 has 0.4 dB and 0.3 dB SNR better than the RLS algorithm with B=4 for MDL and ξ=1 dB and ξ=55 dB, respectively. Full article
(This article belongs to the Special Issue Advanced Fiber Laser Technology and Its Application)
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<p>Complex baseband model of MDM transmission with MIMO equalizer.</p> Full article ">Figure 2
<p>Average symbol–error ratio versus number of training blocks <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>n</mi> </mrow> <mrow> <mi>t</mi> <mi>r</mi> </mrow> </msub> </mrow> </semantics></math> using LMS, RLS, and Adam algorithms with <math display="inline"><semantics> <mrow> <mi>B</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>4</mn> <mo>,</mo> <mn>8</mn> <mo>,</mo> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>16</mn> </mrow> </semantics></math>, assuming <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.1</mn> <mo>,</mo> <msub> <mrow> <mo> </mo> <mi>β</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> <mo>=</mo> <mn>0.99999</mn> <mo>,</mo> <mo> </mo> <msub> <mrow> <mi>β</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> <mo>=</mo> <mn>0.99</mn> <mo>,</mo> <mo> </mo> <mi>ε</mi> <mo>=</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>8</mn> </mrow> </msup> </mrow> </semantics></math>, <span class="html-italic">κ</span> = 0.999, <math display="inline"><semantics> <mrow> <mi>μ</mi> <mo>=</mo> <mn>1.5</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>5</mn> </mrow> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ξ</mi> <mo>=</mo> <mn>1</mn> <mo> </mo> <mi mathvariant="normal">d</mi> </mrow> </semantics></math>B, and <math display="inline"><semantics> <mrow> <mi>D</mi> <mo>=</mo> <mn>12</mn> </mrow> </semantics></math>.</p> Full article ">Figure 3
<p>Average symbol–error ratio versus number of training blocks <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">n</mi> </mrow> <mrow> <mi mathvariant="normal">t</mi> <mi mathvariant="normal">r</mi> </mrow> </msub> </mrow> </semantics></math> using LMS, RLS, and Adam algorithms with <math display="inline"><semantics> <mrow> <mi>B</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mo> </mo> <mn>4</mn> <mo>,</mo> <mo> </mo> <mn>8</mn> <mo>,</mo> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>16</mn> </mrow> </semantics></math>, assuming <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.1</mn> <mo>,</mo> <msub> <mrow> <mo> </mo> <mi>β</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> <mo>=</mo> <mn>0.99999</mn> <mo>,</mo> <mo> </mo> <msub> <mrow> <mi>β</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> <mo>=</mo> <mn>0.999</mn> <mo>,</mo> <mo> </mo> <mi>ε</mi> <mo>=</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>8</mn> </mrow> </msup> </mrow> </semantics></math>, <span class="html-italic">κ</span> = 0.999, <math display="inline"><semantics> <mrow> <mi>μ</mi> <mo>=</mo> <mn>7.2</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>6</mn> </mrow> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ξ</mi> <mo>=</mo> <mn>5</mn> <mo> </mo> <mi mathvariant="normal">d</mi> </mrow> </semantics></math>B, and <math display="inline"><semantics> <mrow> <mi>D</mi> <mo>=</mo> <mn>12</mn> </mrow> </semantics></math>.</p> Full article ">Figure 4
<p>Average symbol–error ratio versus SNR in dB using LMS, RLS, and Adam algorithms, assuming <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.1</mn> <mo>,</mo> <msub> <mrow> <mo> </mo> <mi>β</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> <mo>=</mo> <mn>0.99999</mn> <mo>,</mo> <mo> </mo> <msub> <mrow> <mi>β</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> <mo>=</mo> <mn>0.99</mn> <mo>,</mo> <mo> </mo> <mi>ε</mi> <mo>=</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>8</mn> </mrow> </msup> <mo>,</mo> <mo> </mo> </mrow> </semantics></math><span class="html-italic">κ</span> = 0.999, <math display="inline"><semantics> <mrow> <mi>μ</mi> <mo>=</mo> <mn>1.5</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>5</mn> </mrow> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ξ</mi> <mo>=</mo> <mn>1</mn> <mo> </mo> <mi mathvariant="normal">d</mi> </mrow> </semantics></math>B and <math display="inline"><semantics> <mrow> <mi>D</mi> <mo>=</mo> <mn>12</mn> </mrow> </semantics></math> (solid line), and <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.1</mn> <mo>,</mo> <msub> <mrow> <mo> </mo> <mi>β</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> <mo>=</mo> <mn>0.99999</mn> <mo>,</mo> <mo> </mo> <msub> <mrow> <mi>β</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> <mo>=</mo> <mn>0.999</mn> <mo>,</mo> <mo> </mo> <mi>ε</mi> <mo>=</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>8</mn> </mrow> </msup> </mrow> </semantics></math>, <span class="html-italic">κ</span> = 0.999, <math display="inline"><semantics> <mrow> <mi>μ</mi> <mo>=</mo> <mn>7.2</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>6</mn> </mrow> </msup> <mo> </mo> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>ξ</mi> <mo>=</mo> <mn>5</mn> <mo> </mo> <mi mathvariant="normal">d</mi> </mrow> </semantics></math>B, and <math display="inline"><semantics> <mrow> <mi>D</mi> <mo>=</mo> <mn>12</mn> </mrow> </semantics></math> (dotted line).</p> Full article ">
19 pages, 8765 KiB  
Article
Spatial Multiplexing Holography for Multi-User Visible Light Communication
by Chaoxu Chen, Yuan Wei, Haoyu Zhang, Ziyi Zhuang, Ziwei Li, Chao Shen, Junwen Zhang, Haiwen Cai, Nan Chi and Jianyang Shi
Photonics 2025, 12(2), 160; https://doi.org/10.3390/photonics12020160 - 17 Feb 2025
Viewed by 194
Abstract
Given the burgeoning necessity for high-speed, efficient, and secure wireless communication in 6G, visible light communication (VLC) has emerged as a fervent subject of discourse within academic and industrial circles alike. Among these considerations, it is imperative to construct scalable multi-user VLC systems, [...] Read more.
Given the burgeoning necessity for high-speed, efficient, and secure wireless communication in 6G, visible light communication (VLC) has emerged as a fervent subject of discourse within academic and industrial circles alike. Among these considerations, it is imperative to construct scalable multi-user VLC systems, meticulously addressing pivotal issues such as power dissipation, alignment errors, and the safeguarding of user privacy. However, traditional methods like multiplexing holography (MPH) and multiple focal (MF) phase plates have shown limitations in meeting these diverse requirements. Here, we propose a novel spatial multiplexing holography (SMH) theory, a comprehensive solution that overcomes existing hurdles by enabling precise power allocation, self-designed power coverage, and secure communication through orbital angular momentum (OAM). The transformative potential of SMH is demonstrated through simulations and experimental studies, showcasing its effectiveness in power distribution within systems of VR glasses users, computer users, and smartphone users; enhancing power coverage with an 11.6 dB improvement at coverage edges; and securing data transmission, evidenced by error-free 1080P video playback under correct OAM keys. Our findings illustrate the superior performance of SMH in facilitating seamless multi-user communication, thereby establishing a new benchmark for future VLC systems in the 6G landscape. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Optical Wireless Communication)
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<p>(<b>a</b>) Scenario of multi-user system in VLC; (<b>b</b>) Sketch of power allocation; (<b>c</b>) Sketch of power coverage; (<b>d</b>) Sketch of OAM secure communication.</p> Full article ">Figure 2
<p>Application of power allocation holography in projection.</p> Full article ">Figure 3
<p>(<b>a</b>) Process of generating SMH for power allocation; (<b>b</b>) Process of generating SMH for power coverage; (<b>c</b>) Process of generating SMH for OAM secure communication.</p> Full article ">Figure 4
<p>Schematic diagram of precise transmission space sampling. (<b>a</b>) Transmission process without pre-control; (<b>b</b>) Transmission process with pre-control.</p> Full article ">Figure 5
<p>(<b>a</b>) Simulation results for power allocation; (<b>b</b>) Convergence line of GA; (<b>c</b>) Simulation results for power coverage under MF method; (<b>d</b>) Simulation results for power coverage under SMH.</p> Full article ">Figure 6
<p>(<b>a</b>) Simulation of optical field at receiver plane under SMH and conventional method; (<b>b</b>) Power trend of user encoded with OAM modes <span class="html-italic">l</span> = 20 under different OAM keys; (<b>c</b>) Simulation results for OAM secret communication.</p> Full article ">Figure 7
<p>Experimental setup. (<b>a</b>) Experiment platform; (<b>b</b>) Signal processing.</p> Full article ">Figure 8
<p>Experimental results for power allocation. (<b>a</b>) Data rate curve with ROP; (<b>b</b>) One frame of 4K video received under MPH and SMH; (<b>c</b>) BER of each row in the first frame; (<b>d</b>) Mean BER of each second of the video; (<b>e</b>) Working point test for User 1; (<b>f</b>) Working point test for User 2; (<b>g</b>) Working point test for User 3.</p> Full article ">Figure 9
<p>Experimental results for power coverage. (<b>a</b>) User 1’s ROP trend with XoY offset; (<b>b</b>) User 2’s ROP trend with XoY offset; (<b>c</b>) User 3’s ROP trend with XoY offset; (<b>d</b>) Coverage area diameter of 3 users under MF and SMH; (<b>e</b>) Data rate trend with XoY offset of three users; (<b>f</b>) CCD recording at User 1’s plate under different methods; (<b>g</b>) CCD recording at User 2’s plate under different methods; (<b>h</b>) CCD recording at User 3’s plate under different methods; (<b>i</b>) MSE and SSIM of recordings under different methods.</p> Full article ">Figure 10
<p>Experimental results for OAM secure communication. (<b>a</b>) ROP of three users with different OAM keys; (<b>b</b>) Data rate of three users with different OAM keys; (<b>c</b>) CCD recording of three users; (<b>d</b>) One frame of a 1080P video received by User 3 under different OAM keys.</p> Full article ">
18 pages, 5778 KiB  
Article
High-Accuracy Pseudo-Random Code Laser Ranging Method Based on Data Shifting and Parameter Calibration of Phase Discriminator
by Chaoyang Li, Fei Yang, Jianfeng Sun, Zhiyong Lu, Yu Zhou, Chenxiang Qian and Weibiao Chen
Photonics 2025, 12(2), 159; https://doi.org/10.3390/photonics12020159 - 17 Feb 2025
Viewed by 268
Abstract
High-accuracy and high-precision inter-satellite ranging enhances the orbital accuracy of the Global Navigation Satellite System and facilitates Autonomous Navigation without requiring ground stations. This study proposes a novel phase discrimination method based on pseudo-random code phase modulation coherent laser ranging, which solves the [...] Read more.
High-accuracy and high-precision inter-satellite ranging enhances the orbital accuracy of the Global Navigation Satellite System and facilitates Autonomous Navigation without requiring ground stations. This study proposes a novel phase discrimination method based on pseudo-random code phase modulation coherent laser ranging, which solves the problem of mutual restriction between ranging accuracy and ranging precision in the traditional method. The early–late correlation peaks are obtained via data shifting, while the early and late codes remain unchanged. The characteristic parameters of the early–late discriminator model are calibrated by the actual ranging system, which achieves enhanced ranging accuracy and precision simultaneously. Ground test results indicate that for the static target, the accuracy of the distance measurement is 0.56 mm, while the precision is 0.34 mm. The ranging accuracy of the proposed method has improved by a factor of 91 compared to the traditional method. For dynamic targets, the accuracies of the distance and speed measurements are 0.38 mm and 0.44 mm/s, respectively. Full article
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<p>Schematic of distance measurement and flowchart of traditional and proposed distance measurement methods. (<b>a</b>) Schematic of distance measurement. (<b>b</b>) Traditional ranging flowchart. (<b>c</b>) Proposed ranging flowchart.</p> Full article ">Figure 2
<p>Correlation functions of pseudo-random codes with different bandwidths.</p> Full article ">Figure 3
<p>Calibration of the characteristic parameters.</p> Full article ">Figure 4
<p>Velocity solving flowchart.</p> Full article ">Figure 5
<p>Z values and linear fitting.</p> Full article ">Figure 6
<p>Measurement results of 40 steps of 25 mm. (<b>a</b>) Ranging accuracy. (<b>b</b>) Histogram of ranging results.</p> Full article ">Figure 7
<p>Standard deviations of the distance measurements at the 41 positions.</p> Full article ">Figure 8
<p>Measurement results of the accumulated distance of 40 steps. (<b>a</b>) Mean value of the measured distance at 41 positions. (<b>b</b>) Deviation of the measured distance at 41 positions.</p> Full article ">Figure 9
<p>Three groups of measurements of the distance of the stationary target. (<b>a</b>) The three groups of measurements. (<b>b</b>) Deviations after subtracting the average of the three groups of measurements.</p> Full article ">Figure 10
<p>Measurement results for the relative distances of the moving target. (<b>a</b>) Ranging results. (<b>b</b>) Deviations between the measured and theoretical distances.</p> Full article ">Figure 11
<p>Velocity measurements for the moving target.</p> Full article ">Figure 12
<p>Relationship between the received optical power and the ranging precision (or distance).</p> Full article ">Figure 13
<p>Time domain and frequency domain plots of pseudo-random code and theoretical early–late discrimination model. (<b>a</b>) Time-domain plot. (<b>b</b>) Frequency-domain plot. (<b>c</b>) Theoretical early–late discrimination model.</p> Full article ">Figure 14
<p>Relationship between the early–late discrimination model and bandwidth and relationship between ranging precision and bandwidth and SNR. (<b>a</b>) Relationship between the early–late discrimination model and bandwidth. (<b>b</b>) Relationship between ranging precision and bandwidth and SNR.</p> Full article ">
12 pages, 10977 KiB  
Article
Behavior of Finite-Energy Fresnel–Bessel Beams in Long Free-Space Optical Communication Links
by Cemre Irem Akcan, Mert Bayraktar, Symeon Chatzinotas and Kholoud Elmabruk
Photonics 2025, 12(2), 158; https://doi.org/10.3390/photonics12020158 - 16 Feb 2025
Viewed by 262
Abstract
In this paper, we studied the propagation properties of a finite-energy Fresnel–Bessel beam (FEFBB) propagating in a turbulent atmosphere. We analyzed and investigated the system parameters’ impact on the kurtosis parameters and the beam size. The results show that the FEFBB profiles turn [...] Read more.
In this paper, we studied the propagation properties of a finite-energy Fresnel–Bessel beam (FEFBB) propagating in a turbulent atmosphere. We analyzed and investigated the system parameters’ impact on the kurtosis parameters and the beam size. The results show that the FEFBB profiles turn into Gaussian-like profiles as they propagate through longer links. In long links, higher-order FEFBBs are sharper than lower-order beams. However, FEFBBs with higher Fresnel numbers are flatter than those with lower Fresnel numbers. On the other hand, beams with higher orders and bigger radii spread less. Moreover, FEFBBs have the advantage of keeping the beam size smaller than that in other classical beams. We anticipate our results will be useful for free-space optics (FSO) designers. Full article
(This article belongs to the Special Issue Emerging Technologies for 6G Space Optical Communication Networks)
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<p>Intensity profiles of FEFBBs at the source plane with different beam orders at (<b>a</b>) <span class="html-italic">N</span> = 3.6 and (<b>b</b>) <span class="html-italic">N</span> = 10.</p> Full article ">Figure 2
<p>The received intensity of an FEFBB with N = 3.6 at different propagation distances: (<b>a</b>) <span class="html-italic">n</span> = 0, (<b>b</b>) <span class="html-italic">n</span> = 1.5, (<b>c</b>) <span class="html-italic">n</span> = 7, and (<b>d</b>) <span class="html-italic">n</span> = 10.</p> Full article ">Figure 3
<p>The received intensity of the FEFBB with N = 7.2 at different propagation distances: (<b>a</b>) <span class="html-italic">n</span> = 0, (<b>b</b>) <span class="html-italic">n</span> = 1.5, (<b>c</b>) <span class="html-italic">n</span> = 7, and (<b>d</b>) <span class="html-italic">n</span> = 10.</p> Full article ">Figure 4
<p>Impact of fundamental beam waist on the variation in the FEFBB’s beam size vs. the propagation distance under different turbulence levels, where <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">N</mi> <mo>=</mo> <mn>7.2</mn> <mo>,</mo> </mrow> </semantics></math> (<b>a</b>) <span class="html-italic">n</span> = 0, (<b>b</b>) <span class="html-italic">n</span> = 3, and (<b>c</b>) <span class="html-italic">n</span> = 10.</p> Full article ">Figure 5
<p>Impact of fundamental beam waist on the variation in the FEFBBs’ kurtosis parameter vs. the propagation distance under different turbulence levels, where <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">N</mi> <mo>=</mo> <mn>7.2</mn> <mo>,</mo> </mrow> </semantics></math> (<b>a</b>) <span class="html-italic">n</span> = 0, (<b>b</b>) <span class="html-italic">n</span> = 3, and (<b>c</b>) <span class="html-italic">n</span> = 10.</p> Full article ">Figure 6
<p>The variation in the FEFBBs’ beam size against the propagation distance at different beam orders, where <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">N</mi> <mo>=</mo> <mn>7.2</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="bold-italic">C</mi> </mrow> <mrow> <mi mathvariant="bold-italic">n</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msubsup> <msup> <mrow> <mo>=</mo> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>14</mn> </mrow> </msup> <msup> <mrow> <mi mathvariant="bold">m</mi> </mrow> <mrow> <mo>−</mo> <mn>2</mn> <mo>/</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>: (<b>a</b>) ⍵ = 0.5 cm and (<b>b</b>) ⍵ = 1.5 cm.</p> Full article ">Figure 7
<p>The variation in the FEFBBs’ beam size against the propagation distance at different beam orders, where <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">N</mi> <mo>=</mo> <mn>7.2</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="bold-italic">C</mi> </mrow> <mrow> <mi mathvariant="bold-italic">n</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msubsup> <msup> <mrow> <mo>=</mo> <mn>2</mn> <mo>×</mo> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>15</mn> </mrow> </msup> <msup> <mrow> <mi mathvariant="bold">m</mi> </mrow> <mrow> <mo>−</mo> <mn>2</mn> <mo>/</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>: (<b>a</b>) ⍵ = 0.5 cm and (<b>b</b>) ⍵ = 1.5 cm.</p> Full article ">Figure 8
<p>The variation in the FEFBBs’ kurtosis parameter against the propagation distance at different beam orders, where <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">N</mi> <mo>=</mo> <mn>7.2</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="bold-italic">C</mi> </mrow> <mrow> <mi mathvariant="bold-italic">n</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msubsup> <msup> <mrow> <mo>=</mo> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>14</mn> </mrow> </msup> <msup> <mrow> <mi mathvariant="bold">m</mi> </mrow> <mrow> <mo>−</mo> <mn>2</mn> <mo>/</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>: (<b>a</b>) ⍵ = 0.5 cm and (<b>b</b>) ⍵ = 1.5 cm.</p> Full article ">Figure 9
<p>The variation in the FEFBBs’ kurtosis parameter against the propagation distance at different beam orders, where <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">N</mi> <mo>=</mo> <mn>7.2</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="bold-italic">C</mi> </mrow> <mrow> <mi mathvariant="bold-italic">n</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msubsup> <msup> <mrow> <mo>=</mo> <mn>2</mn> <mo>×</mo> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>15</mn> </mrow> </msup> <msup> <mrow> <mi mathvariant="bold">m</mi> </mrow> <mrow> <mo>−</mo> <mn>2</mn> <mo>/</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math>: (<b>a</b>) ⍵ = 0.5 cm and (<b>b</b>) ⍵ = 1.5 cm.</p> Full article ">
12 pages, 4571 KiB  
Article
High-Efficiency Lithium Niobate Electro-Optic Modulator with Barium Titanate Cladding on Quartz
by Hongkang Liu, Jianping Li, Weiqin Zheng, Zixin Chen, Jianbo Zhang and Yuwen Qin
Photonics 2025, 12(2), 157; https://doi.org/10.3390/photonics12020157 - 14 Feb 2025
Viewed by 448
Abstract
The thin-film lithium niobate (TFLN)-based electro-optic (EO) modulator is one of the most important devices for optical communications in terms of the advantages of low voltages and large bandwidth. However, the large size of devices limits their applicability in large-scale integrated optical systems, [...] Read more.
The thin-film lithium niobate (TFLN)-based electro-optic (EO) modulator is one of the most important devices for optical communications in terms of the advantages of low voltages and large bandwidth. However, the large size of devices limits their applicability in large-scale integrated optical systems, posing a key challenge in maintaining performance advantages under restricted design space. In this paper, we propose a novel TFLN modulator on a quartz substrate incorporating barium titanate (BaTiO3, BTO) as the cladding material. The device is designed with silicon–lithium niobate (Si-LN) hybrid waveguides for operation at a wavelength of 1.55 µm. After theoretical analysis and parameter optimization, the proposed 10 mm long modulator demonstrates high-efficiency modulation, featuring a low half-wave voltage-length product of 1.39 V·cm, a broad 3 dB EO bandwidth of 152 GHz, and low optical loss. This theoretical model provides a novel design solution for TFLN modulators on quartz substrates. Moreover, it is a promising solution for enhancing the integration of photonic devices on the TFLN platform. Full article
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<p>(<b>a</b>) 3D schematic (not to scale), and (<b>b</b>,<b>c</b>) cross-sectional view of modulator.</p> Full article ">Figure 2
<p>(<b>a</b>) Schematic of coupling section from transition waveguide (shown in blue) to hybrid waveguide (shown in red). (<b>b</b>) Simulated confinement factor in TFLN layer and Si waveguide as a function of Si waveguide width. (<b>c</b>) Transition mode field. (<b>d</b>) Hybrid mode field.</p> Full article ">Figure 3
<p>Simulated electric field and fundamental mode of TFLN modulator with low-<span class="html-italic">ε</span> cladding (<b>a</b>,<b>b</b>) and with BTO cladding (<b>c</b>,<b>d</b>).</p> Full article ">Figure 4
<p>Simulated optical loss and V<sub>π</sub>·L for EO modulators with and without BTO cladding, versus gap between electrodes.</p> Full article ">Figure 5
<p>(<b>a</b>,<b>b</b>) Effects of height variations in BTO and SiO<sub>2</sub> cladding on modulation efficiency and propagation loss. Dotted box indicates region of preferred structure parameters. (<b>c</b>) Effects of width variations in SiO<sub>2</sub> cladding on modulation efficiency and propagation loss.</p> Full article ">Figure 6
<p>(<b>a</b>) Simulation of RF effective index for devices with and without BTO. (<b>b</b>) RF loss. (<b>c</b>) characteristic impedance. (<b>d</b>) EO response and electrical reflection (S<sub>11</sub>).</p> Full article ">Figure 7
<p>Contour maps of RF effective index (<b>a</b>) and characteristic impedance (<b>b</b>) as a function of signal electrode width <span class="html-italic">w</span><sub>s</sub> and thickness <span class="html-italic">h</span><sub>Au</sub>. Width of electrode gap is fixed as 7 μm, and parameters are simulated at 50 GHz. (<b>c</b>) Calculated 3 dB modulation bandwidth.</p> Full article ">
27 pages, 2706 KiB  
Review
Recent Innovations in Retinal Laser Therapy
by Mi Zheng and Yannis M. Paulus
Photonics 2025, 12(2), 156; https://doi.org/10.3390/photonics12020156 - 14 Feb 2025
Viewed by 386
Abstract
The early history of retinal laser therapy began with the observation of solar blindness, leading to the development of various laser technologies for treating retinal diseases. The first retinal photocoagulation machine was developed in 1956, and subsequent advancements introduced ruby and argon lasers. [...] Read more.
The early history of retinal laser therapy began with the observation of solar blindness, leading to the development of various laser technologies for treating retinal diseases. The first retinal photocoagulation machine was developed in 1956, and subsequent advancements introduced ruby and argon lasers. While conventional theories posited that retinal damage was an indispensable prerequisite for therapeutic effects, emergent insights highlight the non-damaging mechanisms, such as photostimulation- and self-repair-related mechanisms. Novel therapies, such as subthreshold micropulse laser (SMPL) and selective retina therapy (SRT), are now being employed alongside innovative delivery systems to improve treatment efficiency and safety. Clinical studies are underway to evaluate the efficacy of these therapies for conditions like diabetic retinopathy and central serous chorioretinopathy. Despite the challenges in standardization and long-term evaluation, these innovations represent significant progress towards safer and more effective laser treatment for retinal diseases. Full article
(This article belongs to the Special Issue New Perspectives in Biomedical Optics and Optical Imaging)
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<p>Timeline of the development of photo-mediated retinal laser therapy.</p> Full article ">Figure 2
<p>Baseline fundus color photography, red-free photography, and fluorescein angiography (FA) (<b>A</b>) of an mETDRS group patient; (<b>B</b>) of the same patient 3 months after mETDRS treatment, showing barely visible burns in the color photograph, although the laser scars can be easily identified in FA; (<b>C</b>) of an HD-SDM group patient before treatment; and (<b>D</b>) of the same patient after HD-SDM treatment, showing that even in FA, micropulse treatment remains nonvisible. Reprinted (adapted) with permission from [<a href="#B57-photonics-12-00156" class="html-bibr">57</a>]. Licensed under CC BY 4.0.</p> Full article ">Figure 3
<p>Navilas fundus imaging and laser treatment device applying a slit-based camera and touchscreen monitor for imaging, planning, and treating fundus changes. Reprinted (adapted) with permission from [<a href="#B166-photonics-12-00156" class="html-bibr">166</a>]. Licensed under CC BY 4.0.</p> Full article ">Figure 4
<p>Scanning laser ophthalmoscopy (Optos) photographs of standard targeted retinal photocoagulation (TRP) treatment burns: (<b>A</b>) Color fundus photograph at 1 hr showing standard intensity of 20 ms TRP burns within a 5 × 5 array. (<b>B</b>) Color image of fundus photograph at 4 weeks showing well-localized and pigmented laser burns within an array. The laser burn spot spacing has increased because of healing of laser lesions and reduction in burn size over time. (<b>C</b>) Optos green-free fundus photograph at 12 weeks showing retinal coverage of TRP laser burns in peripheral retina. There are pretreatment laser titration burns visible nasal and superior to the optic disk. Reprinted (adapted) with permission from [<a href="#B178-photonics-12-00156" class="html-bibr">178</a>]. Licensed under CC BY 4.0.</p> Full article ">Figure 5
<p>Representative PUT results in a rabbit CNV model. (<b>a1</b>–<b>a5</b>) Fundus photographs and (<b>b1</b>–<b>b5</b>) late-phase FA images taken at different observation time points, including Day 0 (immediately before PUT treatment and 2−4 weeks after M&amp;V injection), and Day 3, Day 7, Day 14, and Day 28 after the treatment. (<b>c1</b>–<b>c5</b>) Registered late-phase FA images at different observation time points, where the red circles indicate the treatment area. (<b>d1</b>–<b>d5</b>) Binary images at different observation time points, showing the hyperfluorescent area consistent with the CNV leakage. Reprinted (adapted) with permission from [<a href="#B189-photonics-12-00156" class="html-bibr">189</a>]. Licensed under CC BY 4.0.</p> Full article ">
14 pages, 1621 KiB  
Review
Interband Cascade Lasers from a Historic Perspective to a Future Outlook
by Rui Q. Yang and Michael B. Santos
Photonics 2025, 12(2), 155; https://doi.org/10.3390/photonics12020155 - 13 Feb 2025
Viewed by 649
Abstract
Efficient, reliable, and low-cost mid-infrared interband cascade lasers (ICLs) are needed to meet the growing demands of many useful applications such as chemical sensing, environmental and greenhouse gas monitoring, detection of pipe leaks and explosives, food safety, medical diagnostics, and industrial process control. [...] Read more.
Efficient, reliable, and low-cost mid-infrared interband cascade lasers (ICLs) are needed to meet the growing demands of many useful applications such as chemical sensing, environmental and greenhouse gas monitoring, detection of pipe leaks and explosives, food safety, medical diagnostics, and industrial process control. We review the developments and status of ICLs from a historic perspective, discuss the lessons learnt from experience, and suggest considerations for future research and development. This review endeavors to include the most representative aspects and activities of ICLs, but cannot possibly describe every contribution in the 30 years since the initiation of ICLs. We present an overall picture of the ICL architecture and connect the fundamental principle and underlying physics to future activities. Full article
(This article belongs to the Special Issue The Three-Decade Journey of Quantum Cascade Lasers)
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<p>Schematic illustration of an ICL, in which the dashed lines indicate semi-metallic interfaces where interband tunneling occurs. In other words, electrons (<b><span class="html-italic">e</span><sup>−</sup></b>) and holes (<b><span class="html-italic">h<sup>+</sup></span></b>) are generated internally due to the broken-bandgap alignment at a type-II heterostructure interface. AR is the active region where interband transitions occur to generate photons with an energy of <span class="html-italic">hν</span>. Here, <span class="html-italic">h</span> is Planck’s constant and <span class="html-italic">ν</span> is the frequency.</p> Full article ">Figure 2
<p>Representative milestones in the development of ICLs over three decades from 1994 to 2024.</p> Full article ">Figure 3
<p>Schematic illustration of an ICL in which electron barrier (eB) and hole barrier (hB) layers are inserted in each stage to confine electrons and holes in the active region (AR) while keeping open the interband tunneling channel between adjacent stages.</p> Full article ">
15 pages, 4940 KiB  
Article
Research on Image Motion Compensation Technology in Vehicle-Mounted Photoelectric Servo System
by Mingyang Zhang, Yunjie Teng, Jingyi Fu and Tongyu Liu
Photonics 2025, 12(2), 154; https://doi.org/10.3390/photonics12020154 - 13 Feb 2025
Viewed by 370
Abstract
In order to improve the imaging quality of the vehicle photoelectric servo system, image motion compensation under the vehicle platform is studied. Based on the principle of image motion compensation, combined with coordinate system transformation and velocity vector decomposition, the angular velocity compensation [...] Read more.
In order to improve the imaging quality of the vehicle photoelectric servo system, image motion compensation under the vehicle platform is studied. Based on the principle of image motion compensation, combined with coordinate system transformation and velocity vector decomposition, the angular velocity compensation formula of a fast mirror in dynamic scanning imaging of a vehicle photoelectric servo system is obtained. A discrete sliding mode control algorithm based on the Kalman filter is proposed. The proposed algorithm and the discrete sliding mode control algorithm are simulated and compared to verify the system control performance. The simulation results show that the designed algorithm improves control accuracy by 76.3%, reduces overshoot by 75%, and improves response time by 31.25% compared with the discrete sliding mode control algorithm. The experimental platform is built to verify the experimental results. The experimental results show that the speed stability accuracy of the fast mirror is better than 19 μrad, which is 74.37% higher than that of the traditional control scheme. This study provides a reference for the follow-up study of image motion compensation in a vehicle photoelectric servo system. Full article
(This article belongs to the Special Issue Stable Control Technology and Image Perception Technology in Optoelectronic Servo Systems)
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<p>Vehicle photoelectric servo system imaging model.</p> Full article ">Figure 2
<p>Velocity vector decomposition diagram.</p> Full article ">Figure 3
<p>Coordinate system transformation diagram.</p> Full article ">Figure 4
<p>Servo system control block diagram.</p> Full article ">Figure 5
<p>KF-DSMC control block diagram.</p> Full article ">Figure 6
<p>Step response signal diagram.</p> Full article ">Figure 7
<p>Vibration spectrum of a car traveling at 10 m/s.</p> Full article ">Figure 8
<p>Noise signal diagrams. (<b>a</b>) Process noise signal diagram. (<b>b</b>) Random noise signal diagram.</p> Full article ">Figure 9
<p>Sinusoidal signal tracking diagram.</p> Full article ">Figure 10
<p>Stabilization accuracy error plot for sinusoidal signals.</p> Full article ">Figure 11
<p>Field experiment diagram. (<b>a</b>) Image motion compensation device diagram and vehicle photoelectric servo system diagram. (<b>b</b>) Image motion compensation device diagram.</p> Full article ">Figure 12
<p>Angular velocity curve of image motion compensation.</p> Full article ">Figure 13
<p>Stabilization accuracy error of fast steering mirror.</p> Full article ">Figure 14
<p>Image motion compensation comparison diagrams. (<b>a</b>) Image without image motion compensation. (<b>b</b>) Image after image motion compensation.</p> Full article ">
16 pages, 4586 KiB  
Article
Optically Referenced Microwave Generator with Attosecond-Level Timing Noise
by Lulu Yan, Jun Ruan, Pan Zhang, Bingjie Rao, Mingkun Li, Zhijing Du and Shougang Zhang
Photonics 2025, 12(2), 153; https://doi.org/10.3390/photonics12020153 - 13 Feb 2025
Viewed by 363
Abstract
Microwave sources based on ultrastable lasers and optical frequency combs (OFCs) exhibit ultralow phase noise and ultrahigh-frequency stability, which are important for many applications. Herein, we present a microwave source that is phase-locked to an ultrastable continuous-wave laser, with a relative frequency instability [...] Read more.
Microwave sources based on ultrastable lasers and optical frequency combs (OFCs) exhibit ultralow phase noise and ultrahigh-frequency stability, which are important for many applications. Herein, we present a microwave source that is phase-locked to an ultrastable continuous-wave laser, with a relative frequency instability of 7 × 10−16 at 1 s. An Er:fiber-based OFC and an optic-to-electronic converter with low residual noise are employed to confer optical frequency stability on the 9.6 GHz microwave signal. Instead of using the normal cascaded Mach–Zehnder interferometer method, we developed a microwave regeneration method for converting optical pulses into microwave signals to further suppress the additional noise in the optic-to-electronic conversion process. The microwave regeneration method employs an optical-to-microwave phase detector based on a fiber-based Sagnac loop to produce the error signal between a 9.6 GHz dielectric resonator oscillator (DRO) and the OFC. The 9.6 GHz microwave (48th harmonic of the comb’s repetition rate) signal with the frequency stability of the ultrastable laser was achieved using a DRO that was phase-locked to the optical comb. Preliminary evaluations showed that the frequency instability of the frequency synthesizer from the optical to the 9.6 GHz microwave signal was approximately 2 × 10−15 at 1 s, the phase noise was −106 dBc Hz−1 at 1 Hz, and the timing noise was approximately 9 as Hz−1/2 (phase noise approx. −125 dBc Hz−1). The 9.6 GHz signal from the photonic microwave source exhibited a short-term relative frequency instability of 2.1 × 10−15 at 1 s, which is 1.5 times better than the previous results. Full article
(This article belongs to the Special Issue New Perspectives in Microwave Photonics)
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<p>The experimental setup of the photonic microwave source, including the ultrastable laser, Er-doped fiber-based OFC, and optic-to-electronic converter.</p> Full article ">Figure 2
<p>Experimental setup of the ultrastable laser. The red lines indicate the free space optical path, the green lines indicate the fiber optical path, and the black dash lines represent the electric path. PM: polarization-maintaining fiber; CO: collimator; <math display="inline"><semantics> <mi>λ</mi> </semantics></math>/2: half-wave plate; <math display="inline"><semantics> <mi>λ</mi> </semantics></math>/4: quarter-wave plate; AOM: acousto-optic modulator; DDS: direct digital synthesizer; SM: single-mode fiber; PC: physical contact; APC: angled physical contact; PD: photodiode; APD: avalanche photodiode; M: mirror.</p> Full article ">Figure 3
<p>Schematic diagram of the Er:fiber femtosecond laser frequency comb and the frequency detection/control system for <math display="inline"><semantics> <msub> <mi>f</mi> <mrow> <mi>c</mi> <mi>e</mi> <mi>o</mi> </mrow> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>f</mi> <mi>r</mi> </msub> </semantics></math>. (<b>a</b>) Scheme of the OFC. (<b>b</b>) Scheme of the <math display="inline"><semantics> <msub> <mi>f</mi> <mrow> <mi>c</mi> <mi>e</mi> <mi>o</mi> </mrow> </msub> </semantics></math> detection unit. (<b>c</b>) Scheme of the frequency stabilization system for <math display="inline"><semantics> <msub> <mi>f</mi> <mrow> <mi>c</mi> <mi>e</mi> <mi>o</mi> </mrow> </msub> </semantics></math>. (<b>d</b>) Scheme of the frequency stabilization system for <math display="inline"><semantics> <msub> <mi>f</mi> <mrow> <mi>b</mi> <mi>e</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> </semantics></math>. The blue lines represent the single-mode PM fibers, the red lines represent the optical paths, the pink lines represent the single-mode fibers, and the black lines represent the electrical paths. CO: collimator; <math display="inline"><semantics> <mi>λ</mi> </semantics></math>/2: half-wave plate; PBS: polarizing beam splitter; FR: Faraday rotator; M: reflector mirror; TWDM: wavelength division multiplexer; HNLF: highly nonlinear fiber; LF: loop filter; BPF: band-pass filter; HVA: high-voltage amplifier; PD: photodetector; ÷n: n times frequency divider; ÷n*: 20 times frequency divider in OFC1 and 40 times in OFC2; A: amplifier; PS: power splitter.</p> Full article ">Figure 4
<p>Schematic diagram of the microwave regeneration system. The gray dotted box is the optical-to-microwave phase detector, and <math display="inline"><semantics> <msub> <mi>f</mi> <mi>r</mi> </msub> </semantics></math> is the pulse-repetition rate. The red lines represent the optical fiber paths. The black lines represent the electrical paths. FR: Faraday rotator; QWP: quarter waveplate; CO: coupler; <math display="inline"><semantics> <msub> <mi>f</mi> <mi>r</mi> </msub> </semantics></math>: pulse repetition rate.</p> Full article ">Figure 5
<p>Relative frequency instability and phase noise of the ultrastable laser. (<b>a</b>) Frequency instability of the ultrastable laser. Blue dash line: thermal-noise-limited frequency instability. (<b>b</b>) Phase noise power spectral density of the ultrastable laser. Black line: phase noise of the ultrastable laser. Blue line: thermal noise limit.</p> Full article ">Figure 6
<p>Relative frequency instability and frequency fluctuations of the OFC. (<b>a</b>) In-loop relative frequency instability of <math display="inline"><semantics> <msub> <mi>f</mi> <mrow> <mi>c</mi> <mi>e</mi> <mi>o</mi> </mrow> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>f</mi> <mrow> <mi>b</mi> <mi>e</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> </semantics></math>. (<b>b</b>) Frequency fluctuations and bandwidths of the phase-locked <math display="inline"><semantics> <msub> <mi>f</mi> <mrow> <mi>c</mi> <mi>e</mi> <mi>o</mi> </mrow> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>f</mi> <mrow> <mi>b</mi> <mi>e</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> </semantics></math>. Red lines represent <math display="inline"><semantics> <msub> <mi>f</mi> <mrow> <mi>c</mi> <mi>e</mi> <mi>o</mi> </mrow> </msub> </semantics></math>. Black lines represent <math display="inline"><semantics> <msub> <mi>f</mi> <mrow> <mi>b</mi> <mi>e</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> </semantics></math>.</p> Full article ">Figure 7
<p>Experimental setup for evaluating frequency instability and additional phase noise of the photonic microwave generator. The red lines represent the optical paths, and the black lines represent the electrical paths. DRO: dielectric resonator oscillator; LF: loop filter; PS: power splitter; AMP: amplifier.</p> Full article ">Figure 8
<p>Frequency instability and phase noise of the optic-to-electronic converter. (<b>a</b>) Frequency instability curve. (<b>b</b>) Single sideband (SSB) phase noise power spectral density curve.</p> Full article ">Figure 9
<p>Frequency instability and phase noise of the OFC and optic-to-electronic converter. (<b>a</b>) Frequency instability curve. (<b>b</b>) SSB phase noise power spectral density curve.</p> Full article ">Figure 10
<p>The frequency instability of the photonic microwave generator. The red curve is the frequency instability of the 9.6 GHz microwave signal. The green curve is the frequency instability of the optical divider from the OFC to the 9.6 GHz microwave signal. The blue curve is the frequency instability of the ultrastable laser. The black dotted curve represents the frequency instability of the previously generated 9.54 GHz signal by the photonic microwave generator.</p> Full article ">
13 pages, 4611 KiB  
Article
Performance Enhancement of Planar GaAs Photoconductive Semiconductor Switches by Introducing p-Type Epitaxial Layer
by Jiawei Zong, Yating Shi, Guang Qian, Jinpeng Wang, Zelu Wei, Yuechan Kong, Jingwen Zhang and Tangsheng Chen
Photonics 2025, 12(2), 152; https://doi.org/10.3390/photonics12020152 - 13 Feb 2025
Viewed by 302
Abstract
Gallium arsenide photoconductive semiconductor switches (GaAs PCSSs) have attracted much attention in pulsed power systems and high-power microwave sources. The quality of ohmic contact has a significant impact on their switching performance. In this article, a 100 nm p-type epitaxial layer and Ti/Pt/Au [...] Read more.
Gallium arsenide photoconductive semiconductor switches (GaAs PCSSs) have attracted much attention in pulsed power systems and high-power microwave sources. The quality of ohmic contact has a significant impact on their switching performance. In this article, a 100 nm p-type epitaxial layer and Ti/Pt/Au metal electrodes were introduced into a GaAs PCSS to enhance ohmic contact, resulting in a specific contact resistivity of 3 × 10−4 Ω·cm2. The optimized device exhibited a reduction in dark current from 32.2 μA to 11.7 μA and achieved a peak pulse output of 4 kV under a bias of 8.1 kV. This work provides a new feasible approach for high-power miniaturized solid switches. Full article
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<p>Device structure of GaAs PCSS with p-type epitaxial layer (P-PCSS).</p> Full article ">Figure 2
<p>The fabrication process of P-PCSS.</p> Full article ">Figure 3
<p>Dynamic test circuit of GaAs PCSS; inset: the relative spectral intensity and far-field beam.</p> Full article ">Figure 4
<p>Test results of specific contact resistivity of P-PCSS.</p> Full article ">Figure 5
<p>Metal–p-type GaAs ohmic contact band diagram.</p> Full article ">Figure 6
<p>Leakage current of three types of GaAs PCSSs; inset: the AFM image of the GaAs surface after the wet etching process.</p> Full article ">Figure 7
<p>The optical absorption of PCSS.</p> Full article ">Figure 8
<p>The relationship between biased voltage and amplitude.</p> Full article ">Figure 9
<p>The output waveform of three PCSSs: (<b>a</b>) P-PCSS, (<b>b</b>) SI-PCSS with Ni/Ge/Au electrode, and (<b>c</b>) SI-PCSS with Ti/Pt/Au electrode.</p> Full article ">Figure 10
<p>The relationship between biased voltage and pulse width/rise time for P-PCSS.</p> Full article ">Figure 11
<p>The damage situation for different switches: (<b>a</b>) SI-PCSS with Ni/Ge/Au; inset: damage details of this PCSS; (<b>b</b>) P-PCSS.</p> Full article ">Figure 12
<p>The damage situation for different electrodes in P-PCSS: (<b>a</b>) anode and (<b>b</b>) cathode.</p> Full article ">
9 pages, 1947 KiB  
Communication
A Single-Channel Correction Method for Spectral Responsivity Differences in Detector Arrays
by Yilun Cheng, Fengfu Tan, Gangyu Wang, Yang Li, Laian Qin, Feng He and Zaihong Hou
Photonics 2025, 12(2), 151; https://doi.org/10.3390/photonics12020151 - 13 Feb 2025
Viewed by 358
Abstract
The spectral responsivity of photodetectors exhibits significant variations across different wavelengths. Such variations can induce substantial errors when large-scale detector array modules are employed for the measurement of laser spot parameters. In this regard, a single-channel data correction methodology is proposed herein to [...] Read more.
The spectral responsivity of photodetectors exhibits significant variations across different wavelengths. Such variations can induce substantial errors when large-scale detector array modules are employed for the measurement of laser spot parameters. In this regard, a single-channel data correction methodology is proposed herein to mitigate the spectral responsivity discrepancies within large-scale detector arrays. Specifically, the single-channel incident laser within the detector array is bifurcated and irradiated onto the detector with a coated window mirror and the detector at the original corresponding position, respectively. Subsequently, the correction coefficient is computed based on the single-channel data, thereby effectuating the correction of spectral response differences within the large-scale detection array. Through this approach, the measurement error resulting from the spectral responsivity differences in the detection array measurement system is diminished to less than 2%. Notably, this method is applicable to large-scale detection arrays and is not circumscribed to the domain of laser parameter measurement. Full article
(This article belongs to the Special Issue Laser as a Detection: From Spectral Imaging to LiDAR for Remote Sensing Applications)
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<p>Structure diagram of detector array method.</p> Full article ">Figure 2
<p>Basic structure of spectral synthesis.</p> Full article ">Figure 3
<p>Spectral responsivity curve of the detector.</p> Full article ">Figure 4
<p>The spectral responsivity curve of the system after adding a coated window mirror.</p> Full article ">Figure 5
<p>Single-channel spectral responsivity difference elimination system.</p> Full article ">Figure 6
<p>Detector array target calibration system.</p> Full article ">
15 pages, 3863 KiB  
Article
Floating Multi-Focus Metalens for High-Efficiency Airborne Laser Wireless Charging
by Zheting Meng, Yuting Xiao, Lianwei Chen, Si Wang, Yao Fang, Jiangning Zhou, Yang Li, Dapeng Zhang, Mingbo Pu and Xiangang Luo
Photonics 2025, 12(2), 150; https://doi.org/10.3390/photonics12020150 - 12 Feb 2025
Viewed by 530
Abstract
Laser wireless power transfer (LWPT) offers a transformative approach to wireless energy transmission, addressing critical limitations in unmanned aerial vehicles (UAVs) such as battery energy limitation. However, challenges like beam divergence, non-uniform irradiation, and alignment instability limit its practical application. Here, we present [...] Read more.
Laser wireless power transfer (LWPT) offers a transformative approach to wireless energy transmission, addressing critical limitations in unmanned aerial vehicles (UAVs) such as battery energy limitation. However, challenges like beam divergence, non-uniform irradiation, and alignment instability limit its practical application. Here, we present a lightweight air-floating metalens platform to overcome these barriers. This innovative lens focuses laser beams near the photovoltaic receiver with an energy distribution uniformity across a single spot at the focal plane that is 50 times greater than that of a conventional Gaussian beam spot, achieving a multi-spot energy distribution uniformity of up to 99% theoretically. Experimentally, we achieved 75% uniformity using a metalens sample. Simultaneously, our system maintains superior beam quality within a dynamic range of 4 m and enhances charging efficiency by 1.5 times. Our research provides a robust technical solution to improve UAV endurance, enabling efficient, long-range wireless power transfer and opening broader technological implications. Full article
(This article belongs to the Special Issue Recent Advances in Diffractive Optics)
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<p>(<b>a</b>) Schematic of the metalens designed to generate multiple focal spots. When light beams with arbitrary polarization states are incident, a 3 × 3 array of nine focal spots is formed on the focal plane. The uniformity across the focal spots reaches 99%, while the non-uniformity within each individual focal spot remains below 5; (<b>b</b>) Optimized phase profiles of the metalens used to generate nine focal spots and square-shaped focal spots, respectively; (<b>c</b>) Calculated uniformity of the nine focal spots as a function of the distance from the focal plane. The blue curve shows the trend for a metalens generating Gaussian focal spots. The yellow curve represents the uniformity trend for a metalens generating square focal spots prior to optimization, while the purple curve shows the improved trend after optimization.</p> Full article ">Figure 2
<p>Simulation results of Gaussian beam spots versus optimized metalens square beam spots at the focal plane (The maximum light intensity has been normalized to a unit value.). The focal spot is primarily divided into nine regions, denoted as A1, A2, A3, A4, A5, A6, A7, A8, and A9: (<b>a</b>) Energy distribution of nine Gaussian beam spots; (<b>b</b>) Energy distribution of nine square beam spots; (<b>c</b>) Energy distribution of a single Gaussian beam spot; (<b>d</b>) Energy distribution of a single square beam spot; (<b>e</b>) Comparison of energy proportions between Gaussian and square beam spots across nine sub-regions; (<b>f</b>) Comparison of non-uniformity <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> </mrow> </semantics></math> across the nine sub-regions.</p> Full article ">Figure 3
<p>Measurement of the dynamic range of energy distribution (The maximum light intensity has been normalized to a unit value.): (<b>a</b>) Energy distribution of Gaussian beam spots across various propagation distances; (<b>b</b>) Energy distribution of square beam spots across various propagation distances before optimization; (<b>c</b>) Energy distribution of optimized square beam spots across various propagation distances; (<b>d</b>) Comparison of energy proportions in the sub-regions of optimized square beam spots at different propagation distances; (<b>e</b>) Comparison of non-uniformity (Δ) within individual sub-regions of optimized square beam spots at different propagation distances; (<b>f</b>) Overall illumination uniformity (μ) of optimized square beam spots across various propagation distances.</p> Full article ">Figure 3 Cont.
<p>Measurement of the dynamic range of energy distribution (The maximum light intensity has been normalized to a unit value.): (<b>a</b>) Energy distribution of Gaussian beam spots across various propagation distances; (<b>b</b>) Energy distribution of square beam spots across various propagation distances before optimization; (<b>c</b>) Energy distribution of optimized square beam spots across various propagation distances; (<b>d</b>) Comparison of energy proportions in the sub-regions of optimized square beam spots at different propagation distances; (<b>e</b>) Comparison of non-uniformity (Δ) within individual sub-regions of optimized square beam spots at different propagation distances; (<b>f</b>) Overall illumination uniformity (μ) of optimized square beam spots across various propagation distances.</p> Full article ">Figure 4
<p>Experimental verification of the metalens and floating structure: (<b>a</b>) Schematic diagram of the experimental setup for metalens testing; (<b>b</b>) Comparison between experimental and simulation results of square beam spots at various propagation distances; (<b>c</b>) Experimental results of the overall uniformity (μ) of the beam spots at different propagation distances; (<b>d</b>,<b>e</b>) 3D models of the floating structure; (<b>f</b>,<b>g</b>) Experimental verification images of the balloon-supported floating structure; (<b>h</b>) Laser-transmitted power at different positions of the flexible lens.</p> Full article ">
13 pages, 2725 KiB  
Article
Scintillation Properties of β-Ga2O3 Under the Excitation of Ultra-High-Charge Electron Bunches
by Yulan Liang, Jianhan Sun, Chaoyi Zhang, Tianqi Xu, Haoran Chen, Huaqing Huang, Chenhao Hua, Pengying Wan, Chuanwei Dai, Qingfan Wu, Juntao Liu, Lin Huang, Lin Lin, Huili Tang, Jianming Xue, Jun Xu, Senlin Huang, Bo Liu and Wenjun Ma
Photonics 2025, 12(2), 149; https://doi.org/10.3390/photonics12020149 - 12 Feb 2025
Viewed by 438
Abstract
The performance of ultrafast scintillators under ultrahigh dose rate is highly important for applications utilizing brilliant radiation sources. In this work, the scintillation properties of β-Ga2O3, a high-performance ultrafast wide-bandgap semiconductor scintillator, are systematically investigated under dose rates of [...] Read more.
The performance of ultrafast scintillators under ultrahigh dose rate is highly important for applications utilizing brilliant radiation sources. In this work, the scintillation properties of β-Ga2O3, a high-performance ultrafast wide-bandgap semiconductor scintillator, are systematically investigated under dose rates of 107 to 109 Gy/s for the first time by employing ultrashort high-charge electron bunches (bunch charge from 500 fC to 50 pC) generated from a superconducting radio-frequency accelerator. Our results show that in spite of the ultrahigh dose rate, the scintillation intensity was still linearly proportional to the electron bunch charge. Lifetime analysis reveals a fast decay component ranging from 3 to 4 ns, along with an average lifetime of 20 ns. These findings establish a solid foundation for the application of β-Ga2O3 as the scintillation material for high-charge electron sources such as laser-wakefield accelerated electrons. Full article
(This article belongs to the Special Issue Advances in Free-Electron Radiation Sources and Particle Accelerators: Current Research and Future Directions)
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<p>(<b>a</b>) The instrumental setup for in situ time and spectral measurements of β-Ga<sub>2</sub>O<sub>3</sub> in DC-SRF-II gun beamline at Peking University. (<b>b</b>) The temporal profiles of the electron beam for scintillation time/spectral performance characterization of β-Ga<sub>2</sub>O<sub>3</sub>. (<b>c</b>) Simulated total energy deposition rate of 2 MeV pulsed electron beam with 50 pC charge.</p> Full article ">Figure 2
<p>(<b>a</b>) Optical absorption spectra of β-Ga<sub>2</sub>O<sub>3</sub>. The inset shows the Tauc plot of the bulk crystal. (<b>b</b>) Scintillation time response of β-Ga<sub>2</sub>O<sub>3</sub> excited by 257 nm pulsed laser. (<b>c</b>) The PL spectra measured by 240 nm Xe lamp. The dashed lines represent the Gaussian fitting results, with the red line corresponding to 3.1 eV and the green line corresponding to 3.4 eV. (<b>d</b>) Illustration of the emission paths leading to the observed peaks for PL.</p> Full article ">Figure 3
<p>(<b>a</b>) A plot of log (integrated light intensity) vs. log (pulse charge). Solid lines are the linear fitting curves. (<b>b</b>) Time-resolved decay curves under pulsed electron bunch excitation of different charge levels. (<b>c</b>) The averaged decay time and the fast decay time components for different dose rates derived from different charges in the 10 ps electron bunch.</p> Full article ">Figure 4
<p>(<b>a</b>) Normalized spectral response of β-Ga<sub>2</sub>O<sub>3</sub> under HCEB excitation of 50 pC with its Gaussian fitting results. (<b>b</b>) Normalized SEM CL spectra of β-Ga<sub>2</sub>O<sub>3</sub>. (<b>c</b>) Normalized XEL spectrum of β-Ga<sub>2</sub>O<sub>3</sub>. (<b>d</b>) The ratio of the area difference of 3.4 eV peak for different excitation methods.</p> Full article ">Figure 5
<p>(<b>a</b>) Luminescence spectra of β-Ga<sub>2</sub>O<sub>3</sub> under HCEB excitation of different charge levels. The dashed lines represent the Gaussian fitting results, with the orange line corresponding to 2.8 eV, the red line corresponding to 3.1 eV and the green line corresponding to 3.4 eV. (<b>b</b>). Area ratio of different peaks (3.4 eV, 3.1 eV, 2.8 eV).</p> Full article ">
16 pages, 3941 KiB  
Article
Design of a Tunable Metamaterial Absorption Device with an Absorption Band Covering the Mid-Infrared Atmospheric Window
by Zongliang He, Dong Fang and Yougen Yi
Photonics 2025, 12(2), 148; https://doi.org/10.3390/photonics12020148 - 12 Feb 2025
Viewed by 368
Abstract
We propose a highly efficient broadband tunable metamaterial infrared absorption device. The design is modeled using the three-dimensional finite element method for the absorption device. The results show that the absorption device captures over 90% of the light in the wavelength range from [...] Read more.
We propose a highly efficient broadband tunable metamaterial infrared absorption device. The design is modeled using the three-dimensional finite element method for the absorption device. The results show that the absorption device captures over 90% of the light in the wavelength range from 6.10 μm to 17.42 μm. We utilize VO2’s phase change property to adjust the absorption device, allowing the average absorption level to vary between 20.61% and 94.88%. In this study, we analyze the electromagnetic field distribution of the absorption device at its peak absorption point and find that the high absorption is achieved through both surface plasmon resonance and Fabry–Perot cavity resonance. The structural parameters of the absorption device are fine-tuned through parameter scanning. By comparing our work with previous studies, we demonstrate the superior performance of our design. Additionally, we investigate the polarization angle and incident angle of the absorption device and show that it is highly insensitive to these factors. Importantly, the simple structure of our absorption device broadens its potential uses in photodetection, electromagnetic stealth, and sensing. Full article
(This article belongs to the Special Issue Photonics Metamaterials: Processing and Applications)
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<p>(<b>a</b>) Unit structure of the absorption unit. (<b>b</b>) A panoramic perspective of the unit structure of the absorption device. (<b>c</b>) Profile view unveiling the unit’s structure in the absorption device.</p> Full article ">Figure 2
<p>VO<sub>2</sub>’s conductivity at different temperatures.</p> Full article ">Figure 3
<p>(<b>a</b>) Absorption, reflectance, and transmittance curves of the absorbing device at 342 K. (<b>b</b>) Absorption curves of the absorption device at different temperatures.</p> Full article ">Figure 4
<p>(<b>a</b>) Absorption peaks of 90% or more absorption curves. (<b>b</b>) Effective impedance of the absorption device.</p> Full article ">Figure 5
<p>(<b>a</b>–<b>e</b>) Electric field distribution in the XOY plane at the absorption peak of the absorption device. (<b>f</b>–<b>j</b>) Electric field distribution in the XOZ plane at the absorption peak for the absorption device. (<b>k</b>–<b>o</b>) Magnetic field distribution of the absorption device in the XOZ plane at the absorption peak.</p> Full article ">Figure 6
<p>(<b>a</b>) Absorption spectra of the absorbing device at different cycle lengths. (<b>b</b>) Absorption spectra of the absorption device at different distances between neighboring darts. (<b>c</b>) Absorption spectra of the absorption device at different dart lengths.</p> Full article ">Figure 7
<p>(<b>a</b>) Absorption spectra of the absorption device at different VO<sub>2</sub> thicknesses. (<b>b</b>) Absorption spectra of the absorption device at different SiO<sub>2</sub> thicknesses.</p> Full article ">Figure 8
<p>(<b>a</b>) Surface electric field distribution of the absorbing device in TE mode at an incident wavelength of 6.57 µm. (<b>b</b>) Surface electric field distribution of the absorbing device in TM mode at an incident wavelength of 6.57 µm. (<b>c</b>) Absorption spectra of the absorption device at different polarization angles (0–90°).</p> Full article ">Figure 9
<p>(<b>a</b>) Absorption spectra of the absorbing device in TE mode for different angles of incidence (0–60°). (<b>b</b>) Surface electric field distribution of the absorption device at <math display="inline"><semantics> <mi>θ</mi> </semantics></math> = 0° incidence in TE mode. (<b>c</b>) Surface electric field distribution of the absorption device in TE mode at <math display="inline"><semantics> <mi>θ</mi> </semantics></math> = 60° incidence. (<b>d</b>) Absorption spectra of the absorption device in TM mode at different angles of incidence (0–60°). (<b>e</b>) Surface electric field distribution of the absorption device in TM mode at <math display="inline"><semantics> <mi>θ</mi> </semantics></math> = 0° incidence. (<b>f</b>) Surface electric field distribution of the absorption device in TM mode at <math display="inline"><semantics> <mi>θ</mi> </semantics></math> = 60° incidence.</p> Full article ">Figure 10
<p>Different surface shapes and corresponding absorption curves.</p> Full article ">
11 pages, 3582 KiB  
Article
Link Bandwidth and Transmission Capability of Single-Mode Multi-Aperture Vertical-Cavity Surface-Emitting Lasers at 100 G/Lane and 200 G/Lane over Multimode Fibers
by Xin Chen, Nikolay Ledentsov, Jr., Jason E. Hurley, Oleg Yu. Makarov, Ming-Jun Li and Nikolay Ledentsov
Photonics 2025, 12(2), 147; https://doi.org/10.3390/photonics12020147 - 11 Feb 2025
Viewed by 467
Abstract
Single-mode (SM) vertical-cavity surface-emitting lasers (VCSELs) have often been demonstrated with an unusually long transmission reach at very high data rates while today’s multimode VCSEL transmission has been limited by the fiber modal bandwidth and bandwidth contributed by the VCSEL–chromatic dispersion interaction under [...] Read more.
Single-mode (SM) vertical-cavity surface-emitting lasers (VCSELs) have often been demonstrated with an unusually long transmission reach at very high data rates while today’s multimode VCSEL transmission has been limited by the fiber modal bandwidth and bandwidth contributed by the VCSEL–chromatic dispersion interaction under typical encircled flux launch condition. By using the same launch condition for VCSEL and modal bandwidth measurements, we studied the link bandwidth capability of SM multi-aperture (MA) VCSEL transmission. Using a multimode fiber with modal bandwidth under actual launch conditions moderately lower than OM4 threshold, we observed that the link bandwidth, with contributions from both modal bandwidth and laser–chromatic dispersion interaction, is higher than the corresponding modal bandwidths, which is very counter-intuitive. A detailed analysis reveals that the enhanced link bandwidth is contributed by both narrow laser linewidth and favorable laser–chromatic dispersion interaction. Through the study, we demonstrate that OM4 can meet link bandwidth requirements for 200/100 G/lane transmission over 100/200 m using SM MA VCSELs. Full article
(This article belongs to the Special Issue Next-Generation Vertical-Cavity Surface-Emitting Lasers)
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<p>Optical microscopy image of the light-emitting section of an SM MA VCSEL. The four apertures are positioned in an X-configuration around the central circle.</p> Full article ">Figure 2
<p>(<b>a</b>) Voltage and output power characteristics of the SM MA VCSEL and (<b>b</b>) the spectrum of the SM MA VCSEL.</p> Full article ">Figure 3
<p>The experimental configuration for system and link bandwidth measurements through measuring the S<sub>21</sub> parameter.</p> Full article ">Figure 4
<p>The experimental configuration for modal bandwidth measurements using a narrow linewidth light source.</p> Full article ">Figure 5
<p>EFs measured from two experimental configurations. Two green dots indicate the standard-defined thresholds: one at 4.5 μm, which should be equal to or less than 0.3, and another at 19 μm, which should be equal to or less than 0.86.</p> Full article ">Figure 6
<p>(<b>a</b>) S<sub>21</sub> of the transmission system consisting of SM MA VCSEL, photodiode, and ‘MMF1’; (<b>b</b>) S<sub>21</sub> of the MMF link.</p> Full article ">Figure 7
<p>S<sub>21</sub> of ‘MMF1’ using setup in <a href="#photonics-12-00147-f004" class="html-fig">Figure 4</a> for modal bandwidth contribution.</p> Full article ">Figure 8
<p>(<b>a</b>) S<sub>21</sub> of a transmission system consisting of SM MA VCSEL, photodiode, and ‘MMF2’; (<b>b</b>) S<sub>21</sub> of the fiber link.</p> Full article ">Figure 9
<p>S<sub>21</sub> of the ‘MMF2’ using setup in <a href="#photonics-12-00147-f004" class="html-fig">Figure 4</a> for modal bandwidth contribution.</p> Full article ">Figure 10
<p>(<b>a</b>) Bit error rate (BER) contour for 50 Gb/s NRZ PRBS15 transmission with 2-tap feed-forward equalization at the receiver after 100 m of ‘MMF1’; (<b>b</b>) Bit error rate contour obtained for 200 m of ‘MMF1’ under same configuration. Dark blue color corresponds to BER &lt; 1 × 10<sup>−25</sup>.</p> Full article ">
18 pages, 1807 KiB  
Article
3DVT: Hyperspectral Image Classification Using 3D Dilated Convolution and Mean Transformer
by Xinling Su and Jingbo Shao
Photonics 2025, 12(2), 146; https://doi.org/10.3390/photonics12020146 - 11 Feb 2025
Viewed by 415
Abstract
Hyperspectral imaging and laser technology both rely on different wavelengths of light to analyze the characteristics of materials, revealing their composition, state, or structure through precise spectral data. In hyperspectral image (HSI) classification tasks, the limited number of labeled samples and the lack [...] Read more.
Hyperspectral imaging and laser technology both rely on different wavelengths of light to analyze the characteristics of materials, revealing their composition, state, or structure through precise spectral data. In hyperspectral image (HSI) classification tasks, the limited number of labeled samples and the lack of feature extraction diversity often lead to suboptimal classification performance. Furthermore, traditional convolutional neural networks (CNNs) primarily focus on local features in hyperspectral data, neglecting long-range dependencies and global context. To address these challenges, this paper proposes a novel model that combines CNNs with an average pooling Vision Transformer (ViT) for hyperspectral image classification. The model utilizes three-dimensional dilated convolution and two-dimensional convolution to extract multi-scale spatial–spectral features, while ViT was employed to capture global features and long-range dependencies in the hyperspectral data. Unlike the traditional ViT encoder, which uses linear projection, our model replaces it with average pooling projection. This change enhances the extraction of local features and compensates for the ViT encoder’s limitations in local feature extraction. This hybrid approach effectively combines the local feature extraction strengths of CNNs with the long-range dependency handling capabilities of Transformers, significantly improving overall performance in hyperspectral image classification tasks. Additionally, the proposed method holds promise for the classification of fiber laser spectra, where high precision and spectral analysis are crucial for distinguishing between different fiber laser characteristics. Experimental results demonstrate that the CNN-Transformer model substantially improves classification accuracy on three benchmark hyperspectral datasets. The overall accuracies achieved on the three public datasets—IP, PU, and SV—were 99.35%, 99.31%, and 99.66%, respectively. These advancements offer potential benefits for a wide range of applications, including high-performance optical fiber sensing, laser medicine, and environmental monitoring, where accurate spectral classification is essential for the development of advanced systems in fields such as laser medicine and optical fiber technology. Full article
(This article belongs to the Special Issue Advanced Fiber Laser Technology and Its Application)
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<p>Overall framework of the 3DVT network model.</p> Full article ">Figure 2
<p>ViT encoder with average pooling projection.</p> Full article ">
15 pages, 955 KiB  
Article
Decoding Anomalous Diffusion Using Higher-Order Spectral Analysis and Multiple Signal Classification
by Miguel E. Iglesias Martínez, Òscar Garibo-i-Orts and J. Alberto Conejero
Photonics 2025, 12(2), 145; https://doi.org/10.3390/photonics12020145 - 10 Feb 2025
Viewed by 550
Abstract
Anomalous diffusion is characterized by nonlinear growth in the mean square displacement of a trajectory. Recent advances using statistical methods and recurrent neural networks have made it possible to detect such phenomena, even in noisy conditions. In this work, we explore feature extraction [...] Read more.
Anomalous diffusion is characterized by nonlinear growth in the mean square displacement of a trajectory. Recent advances using statistical methods and recurrent neural networks have made it possible to detect such phenomena, even in noisy conditions. In this work, we explore feature extraction through parametric and non-parametric spectral analysis methods to decode anomalously diffusing trajectories, achieving reduced computational costs compared with other approaches that require additional data or prior training. Specifically, we propose the use of higher-order statistics, such as the bispectrum, and a hybrid algorithm that combines kurtosis with a multiple-signal classification technique. Our results demonstrate that the type of trajectory can be identified based on amplitude and kurtosis values. The proposed methods deliver accurate results, even with short trajectories and in the presence of noise. Full article
(This article belongs to the Special Issue Editorial Board Members' Collection Series: Nonlinear Photonics)
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<p>An example of the bispectrum of an ATTM trajectory. <math display="inline"><semantics> <msub> <mi>f</mi> <mn>1</mn> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>f</mi> <mn>2</mn> </msub> </semantics></math> contain the frequencies of the Fourier transform of the third-order cumulant of the data. The axes represent the bispectral content of each frequency that generates the anomalous diffusion sequence.</p> Full article ">Figure 2
<p>Mean value of the bispectrum for the (<b>a</b>) ATTM and (<b>b</b>) CTRW trajectories.</p> Full article ">Figure 3
<p>Mean value of the bispectrum for: (<b>a</b>) FBM and (<b>b</b>) LW trajectories.</p> Full article ">Figure 4
<p>Mean value of the bispectrum for SBM trajectories.</p> Full article ">Figure 5
<p>Overall behavior of the bispectral amplitude according to sequence length: (<b>a</b>) ATTM, (<b>b</b>) CTRW, (<b>c</b>) FBM, (<b>d</b>) LW, and (<b>e</b>) SBM.</p> Full article ">Figure 6
<p>Probability histogram distribution for each trajectory: (<b>a</b>) ATTM trajectory, (<b>b</b>) CTRW trajectory, (<b>c</b>) FBM, (<b>d</b>) LW, and (<b>e</b>) SBM.</p> Full article ">Figure 7
<p>Results using the MUSIC–kurtosis hybrid method: (<b>a</b>) ATTM trajectory (<b>b</b>) CTRW trayectory.</p> Full article ">Figure 8
<p>Results using the MUSIC–kurtosis hybrid method: (<b>a</b>) FBM trajectory (<b>b</b>) LW trajectory.</p> Full article ">Figure 9
<p>Results using the MUSIC–kurtosis hybrid method for: SBM trajectory.</p> Full article ">Figure 10
<p>Overall behavior of the MUSIC–kurtosis according to sequence length: (<b>a</b>) ATTM, (<b>b</b>) CTRW, (<b>c</b>) FBM, (<b>d</b>) LW, and (<b>e</b>) SBM.</p> Full article ">Figure 11
<p>Probability histogram distribution for each trajectory using the MUSIC–kurtosis algorithm: (<b>a</b>) ATTM trajectory, (<b>b</b>) CTRW trajectory, (<b>c</b>) FBM (<b>d</b>) LW, and (<b>e</b>) SBM.</p> Full article ">
18 pages, 8118 KiB  
Article
Asymmetric Modulation Physical-Layer Network Coding Based on Power Allocation and Multiple Receive Antennas in an OFDM-UWOC Three-User Relay Network
by Yanlong Li, Pengcheng Jiang, Shuaixing Li, Xiao Chen, Qihao He and Tuyang Wang
Photonics 2025, 12(2), 144; https://doi.org/10.3390/photonics12020144 - 10 Feb 2025
Viewed by 401
Abstract
In relay-assisted underwater wireless optical communication (UWOC) systems, the traditional time-division-multiplexed relay forwarding strategy faces high latency and low throughput with the increase of relay users. To address these issues, this paper proposes a multiple receiving antenna power allocation-based bit splicing physical layer [...] Read more.
In relay-assisted underwater wireless optical communication (UWOC) systems, the traditional time-division-multiplexed relay forwarding strategy faces high latency and low throughput with the increase of relay users. To address these issues, this paper proposes a multiple receiving antenna power allocation-based bit splicing physical layer network coding (MRA-PABS-PNC) method in a three-user asymmetric modulated relay-assisted UWOC scenario. MRA-PABS-PNC reduces the number of multiple access time slots by using multi-antenna reception techniques. At the same time, it employs a bit-splicing method to concatenate the data that would normally be transmitted over two-time slots into a longer data stream transmitted in a single time slot, thus reducing the number of broadcast time slots and ultimately improving throughput. Moreover, this paper models and determines the optimal position and angle of the relay node photodetector. Once the relay node is positioned at the optimal location and angle, the system can allocate power to each user node based on the channel state information to overcome the effect of asymmetric channels on PNC coding, thereby further improving system performance. Simulation results show that the method improves the throughput by 100% compared with the existing four-time slot PNC (FT-PNC) method. Full article
(This article belongs to the Special Issue Challenges and Opportunities in Underwater Wireless Optical Communications)
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<p>Relay-assisted UWOC scenario.</p> Full article ">Figure 2
<p>Model of three-user relay UWOC system.</p> Full article ">Figure 3
<p>Block diagram of the relay-assisted UWOC system using the MRA-PABS-PNC method.</p> Full article ">Figure 4
<p>Number of bits carried in each time slot on the ACO-OFDM subcarrier in MRA-PABS-PNC.</p> Full article ">Figure 5
<p>Model of PABS-PNC system.</p> Full article ">Figure 6
<p>Number of bits carried in each time slot on the ACO-OFDM subcarrier in PABS-PNC.</p> Full article ">Figure 7
<p>Relay node placeable region.</p> Full article ">Figure 8
<p>Polar and azimuth angles of PD detectors.</p> Full article ">Figure 9
<p>The optimal angle of the PD.</p> Full article ">Figure 10
<p>BER performance of PABS-PNC in shaded areas.</p> Full article ">Figure 11
<p>The BER performance of PABS-PNC and EPBS−PNC in the placeable region at different SNR. (<b>a</b>) SNR = 20; (<b>b</b>) SNR = 25; (<b>c</b>) SNR = 30.</p> Full article ">Figure 12
<p>BER performance of PABS-PNC system with different polar and azimuth angles. (<b>a</b>) Non−turbulent channel. (<b>b</b>) Turbulent channel.</p> Full article ">Figure 13
<p>BER performance of MRA-PABS-PNC system with different polar and supporting angles. (<b>a</b>) Non-turbulent channel. (<b>b</b>) Turbulent channel.</p> Full article ">Figure 14
<p>Relay node constellation diagram for each step using the PABS-PNC method. (<b>a</b>) The constellation diagram received by the relay node at the first time slot, (<b>b</b>) the constellation diagram received at the second time slot, (<b>c</b>) the constellation diagram of (<b>a</b>) after higher−order PNC mapping, (<b>d</b>) the constellation diagram of (<b>b</b>) after higher−order PNC mapping, and (<b>e</b>) the constellation diagram of (<b>a</b>) sent by the relay node to the subscriber node after bit splicing.</p> Full article ">Figure 15
<p>Number of bits carried in each time slot on the ACO-OFDM subcarrier in MPBS-PNC.</p> Full article ">Figure 16
<p>Relay node constellation diagram for each step using the MPBS-PNC method. (<b>a</b>) The constellation diagram received by the relay node at the first time slot, (<b>b</b>) the constellation diagram received at the second time slot, (<b>c</b>) the constellation diagram of (<b>a</b>) after higher−order PNC mapping, (<b>d</b>) the constellation diagram of (<b>b</b>) after higher−order PNC mapping, and (<b>e</b>) the constellation diagram of (<b>a</b>) sent by the relay node to the subscriber node after bit splicing.</p> Full article ">Figure 17
<p>Relay node constellation diagram for each step using the FT-PNC method. (<b>a</b>) The constellation diagram received by the relay node in a first time slot, (<b>b</b>) the constellation diagram received in a second time slot, (<b>c</b>) the constellation diagram sent by the relay node to the user node in a third time slot after higher−order PNC mapping of (<b>a</b>), and (<b>d</b>) the constellation diagram sent by the relay node to the user node in a fourth time slot after higher−order PNC mapping of (<b>b</b>).</p> Full article ">Figure 18
<p>The BER performance and throughput performance comparison of MPBS-PNC, FT-PNC, PABS-PNC, and MRA-PABS-PNC methods. (<b>a</b>) BER performance comparison; (<b>b</b>) Throughput Performance Comparison.</p> Full article ">
14 pages, 2467 KiB  
Article
Theoretical Comparative Study on the Efficiency of High-Power Long-Distance Laser Power Transmission for Flight Systems
by Songyang Liu, Wenning Xu, Rongqing Tan, Fangjin Ning and Zhiyong Li
Photonics 2025, 12(2), 143; https://doi.org/10.3390/photonics12020143 - 10 Feb 2025
Viewed by 426
Abstract
Wireless power transmission has become a research hotspot in the field of energy transmission, in which laser power transmission is one of the best methods for long-distance wireless transmission. Since laser has the advantages of high directivity, high energy density and no electromagnetic [...] Read more.
Wireless power transmission has become a research hotspot in the field of energy transmission, in which laser power transmission is one of the best methods for long-distance wireless transmission. Since laser has the advantages of high directivity, high energy density and no electromagnetic interference, laser power transmission technology can be applied to the energy supply of unmanned aerial vehicles (UAVs), micro-vehicles, airships and other flight systems. Long-distance laser power transmission can enable high-altitude flight systems to operate continuously without the need to return to the base station for charging, im-proving their operational efficiency. Therefore, high-altitude flight systems have a demand for laser power transmission. However, the commonly used lasers in laser power transmission are semiconductor lasers and fiber lasers, which are only suitable for short-distance transmission of about 1 km. In this paper, taking high-flying UAVs as an example, the transmission efficiency of different lasers used for laser power transmission is analyzed theoretically, and the results show that the diode pumped alkali vapor laser (DPAL) has a high transmission efficiency in high-power long-distance laser power transmission. The transmission efficiency of rubidium lasers which is 1.5 to 4 times that of other lasers can reach 21.94%, which illustrates that DPAL is expected to become a new type of laser source in laser power transmission technology. Full article
(This article belongs to the Special Issue Advanced Lasers and Their Applications, 2nd Edition )
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<p>Schematic of a laser power transmission system for a UAV.</p> Full article ">Figure 2
<p>Schematic of laser emission and reception.</p> Full article ">Figure 3
<p>Relationships between transmitting and receiving efficiency and far-field divergence.</p> Full article ">Figure 4
<p>Schematic of the laser transmission.</p> Full article ">Figure 5
<p>Relationships between atmospheric transmittance of individual lasers and altitude under different aerosol conditions: (<b>a</b>) rural, VIS = 23 km; (<b>b</b>) rural, VIS = 5 km; (<b>c</b>) maritime, VIS = 23 km; (<b>d</b>) urban, VIS = 5 km.</p> Full article ">Figure 6
<p>Relationships between atmospheric transmittance of individual lasers and VIS.</p> Full article ">Figure 7
<p>Relationships between atmospheric transmittance of individual lasers and elevation.</p> Full article ">Figure 8
<p>Relationships between photovoltaic conversion efficiency and wavelength.</p> Full article ">
17 pages, 9313 KiB  
Article
Quasi-Invariance of Scattering Properties of Multicellular Cyanobacterial Aggregates
by Chunyang Ma, Qian Lu and Yen Wah Tong
Photonics 2025, 12(2), 142; https://doi.org/10.3390/photonics12020142 - 10 Feb 2025
Viewed by 403
Abstract
The radiative/scattering properties of cyanobacterial aggregates are crucial for understanding microalgal cultivation. This study analyzed the scattering matrix elements and cross-sections of cyanobacterial aggregates using the discrete dipole approximation (DDA) method. A stochastic random walk approach was adopted to generate a force-biased packing [...] Read more.
The radiative/scattering properties of cyanobacterial aggregates are crucial for understanding microalgal cultivation. This study analyzed the scattering matrix elements and cross-sections of cyanobacterial aggregates using the discrete dipole approximation (DDA) method. A stochastic random walk approach was adopted to generate a force-biased packing model for multicellular filamentous cyanobacterial aggregates. The effects of the shape and size of multicellular cyanobacterial aggregates on their scattering properties were investigated in this work. The possibility of invariance in the scattering properties of cyanobacterial aggregates was explored. The invariance interpretation intuitively represented the radiative property characteristics of the aggregates. The presented results show that the ratios of the matrix elements of cyanobacterial aggregates are nearly shape-, size-, and wavelength-invariant. The extinction and absorption cross-sections (EACSs) per unit volume exhibited shape and approximate size invariance for cyanobacterial aggregates, respectively. The absorption cross-section of aggregates is not merely a volumetric phenomenon for aggregates that exceed a certain size. Furthermore, the absorption cross-sections per unit volume are independent of the volumetric distribution of the microalgae cells. The invariance interpretation presents crucial characteristics of the scattering properties of cyanobacterial aggregates. The existence of invariance greatly improves our understanding of the scattering properties of microalgal aggregates. The scattering properties of microalgal aggregates are the most critical aspects of light propagation in the design, optimization, and operation of photobioreactors. Full article
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<p>Micrographs of <span class="html-italic">Nostoc</span> sp. (<b>a</b>) 40× and (<b>b</b>) 100× colonies resembling aggregates.</p> Full article ">Figure 2
<p>Realizations for packed microalgae aggregates. The following are typical parameters: number of samples, <math display="inline"><semantics> <mrow> <mi>n</mi> </mrow> </semantics></math> = 30, for each chain and bending parameters, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>κ</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math> = 5 and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>κ</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> = 5, are the dependability metrics in the desired directions. The volume fractions are (<b>a</b>) 37.9%, and (<b>b</b>) 44.8%.</p> Full article ">Figure 3
<p>Realizations for Gaussian spherical-shaped microalgae aggregates systems with a power-law index of <math display="inline"><semantics> <mrow> <mi>ν</mi> </mrow> </semantics></math> = 3.5, a truncated degree of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>l</mi> </mrow> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> </mrow> </semantics></math> = 50, and a relative standard deviations of radial distances <math display="inline"><semantics> <mrow> <mi>σ</mi> </mrow> </semantics></math> = 0.05 and 0.10 (from left to right). The common parameters of microalgae aggregates are the same as in the previous, and volume fractions are (<b>a</b>) 45.5% and (<b>b</b>) 45.4%.</p> Full article ">Figure 4
<p>Convergence verification of DDA solutions for dpl value, (<b>a</b>) <span class="html-italic">S</span><sub>11</sub>, (<b>b</b>) −<span class="html-italic">S</span><sub>12</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>c</b>) <span class="html-italic">S</span><sub>22</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>d</b>) <span class="html-italic">S</span><sub>33</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>e</b>) <span class="html-italic">S</span><sub>34</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>f</b>) <span class="html-italic">S</span><sub>44</sub>/S<sub>11</sub>.</p> Full article ">Figure 5
<p>Spectral complex refractive index of microalgae cells, (<b>a</b>) spectral refractive index, (<b>b</b>) spectral absorption index.</p> Full article ">Figure 6
<p>Scattering matrix elements of spherical, cubical, and Gauss sphere-shaped aggregates for different sizes, (<b>a</b>) −<span class="html-italic">S</span><sub>12</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>b</b>) <span class="html-italic">S</span><sub>33</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>c</b>) <span class="html-italic">S</span><sub>44</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>d</b>) <span class="html-italic">S</span><sub>22</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>e</b>) <span class="html-italic">S</span><sub>34</sub>/<span class="html-italic">S</span><sub>11</sub>.</p> Full article ">Figure 7
<p>Cross-sections per unit volume of the colonies of microalgae aggregates for different sizes, (<b>a</b>) extinction cross-section, (<b>b</b>) absorption cross-section.</p> Full article ">Figure 8
<p>Cross-sections per unit volume of the colonies of microalgae aggregates for different shapes, (<b>a</b>) extinction cross-section, (<b>b</b>) absorption cross-section.</p> Full article ">Figure 9
<p>Cross-sections per unit volume of the colonies of microalgae aggregates with equivalent volume, (<b>a</b>) extinction cross-section, (<b>b</b>) absorption cross-section.</p> Full article ">Figure 10
<p>Mueller matrix elements of colonies of microalgae aggregates, (<b>a</b>) <span class="html-italic">S</span><sub>11</sub>, (<b>b</b>) −<span class="html-italic">S</span><sub>12</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>c</b>) <span class="html-italic">S</span><sub>22</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>d</b>) <span class="html-italic">S</span><sub>33</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>e</b>) <span class="html-italic">S</span><sub>34</sub>/<span class="html-italic">S</span><sub>11</sub>, (<b>f</b>) <span class="html-italic">S</span><sub>44</sub>/<span class="html-italic">S</span><sub>11</sub>.</p> Full article ">Figure 11
<p>Internal fields of colonies of microalgae aggregates: upper panel for <span class="html-italic">z</span> = 0 plane and lower panel for <span class="html-italic">y</span> = 0 plane. Incident linearized polarized light at the propagation of <span class="html-italic">z</span> direction, (<b>a</b>,<b>d</b>) 440 nm, (<b>b</b>,<b>e</b>) 445 nm, and (<b>c</b>,<b>f</b>) 450 nm.</p> Full article ">Figure 11 Cont.
<p>Internal fields of colonies of microalgae aggregates: upper panel for <span class="html-italic">z</span> = 0 plane and lower panel for <span class="html-italic">y</span> = 0 plane. Incident linearized polarized light at the propagation of <span class="html-italic">z</span> direction, (<b>a</b>,<b>d</b>) 440 nm, (<b>b</b>,<b>e</b>) 445 nm, and (<b>c</b>,<b>f</b>) 450 nm.</p> Full article ">
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