Editor’s Choice Articles

To meet the increasing demands for data, elastic optical networks (EONs) require highly efficient resource management. While classical Routing and Spectrum Assignment (RSA) algorithms establish a path and allocate spectrum, advanced versions such as Routing, Modulation-format-selection, and Spectrum Assignment (RMSA) also optimize modulation format selection. However, these approaches often lack adaptability to diverse network aspects. The hybrid routing and spectrum assignment (HRSA) algorithm offers a more flexible and robust approach by providing multiple choices between route (resource savings) and spectrum prioritization (fragmentation mitigation and network load balancing) for each network node pair. Despite its potential, the adaptive nature of HRSA introduces complexity, and the influence of topological features on its decisions remains not fully understood. This knowledge gap hinders the ability to optimize network design and resource allocation fully. This paper examines how topological features influence HRSA’s adaptive decisions regarding routing and spectrum assignment prioritization for source-destination node pairs in EONs. By employing machine learning approaches—Decision Tree (DT), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—we model and identify the key topological features that influence HRSA’s decision-making. Then, we compare the models generated by each approach and extract insights using an a posteriori analysis technique to evaluate feature importance. Our results show the algorithm’s behavior is highly predictable (over 91% accuracy), with decisions driven primarily by the network’s structure and node metrics. This work advances the understanding of how topological features influence the RSA problem. Full article

Background: This narrative review aims to assess multiple strategies available to evaluate and manage corneal astigmatism in the context of cataract surgery, with a focus on the surgical techniques, intraocular lens (IOL) selection, and the integration of advanced new technologies. Methods: A narrative review based on a literature search in PubMed/MEDLINE and the Cochrane Library, covering publications from 1990 to 2025, was conducted. Eligible studies included randomized controlled trials, observational studies, prospective and retrospective analyses, and systematic reviews. Key search terms included “astigmatism”, “cataract surgery”, “keratometry”, and “refraction.” Studies were screened and selected by two independent reviewers. Results: Corneal astigmatism is the most common form of astigmatism. While the anterior corneal astigmatism plays a more important role, the posterior corneal astigmatism and the posterior-to-anterior corneal ratio (Gullstrand ratio) can impact the postoperative refractive results in a very important way. While planning the cataract surgery, surgically induced astigmatism (SIA), especially on the posterior cornea, must be taken into consideration. Various approaches, such as opposite clear corneal incisions (OCCIs), toric intraocular lens (IOLs), intraoperative aberrometry, and the integration of artificial intelligence and robotic-assisted surgery, are increasing the precision of astigmatism correction and surgical outcomes. Conclusions: Individualized surgical planning and precise measurement are key factors in reducing residual astigmatism and obtaining the best visual outcomes in patients with corneal astigmatism undergoing cataract surgery. By taking into consideration the posterior corneal data, refining IOL calculations, and embracing the rapidly developing technological innovations, patient satisfaction and visual quality can be substantially improved, and the predictability of the surgical outcome can be enhanced. Full article

Functional Optical Balance (FOB) is a novel personalized strategy for intraocular lens (IOL) selection in cataract surgery, designed to reconcile the trade-off between optical quality and spectacle independence. FOB is a core concept aiming to maximize visual performance by treating the two eyes as a synergistic pair. One eye (often the dominant eye) is optimized for pristine optical quality (typically distance vision with a high-contrast monofocal or low-add IOL). In contrast, the fellow eye is optimized for extended depth of focus and pseudoaccommodation (using an extended depth-of-focus or multifocal/trifocal IOL) to reduce dependence on glasses. This review introduces the rationale and theoretical basis for FOB, including the interplay of depth of focus and optical aberrations, binocular summation, ocular dominance, and neuroadaptation. We discuss the clinical implementation of FOB: how the first-eye results guide the second-eye IOL choice in a tailored “mix-and-match” approach, as well as practical workflow considerations such as patient selection, ocular measurements, and decision algorithms. We also review current evidence from the literature on asymmetric IOL combinations (e.g., monofocal plus multifocal, or EDOF plus trifocal), highlighting visual outcomes, patient satisfaction, and remaining evidence gaps. Overall, FOB represents a paradigm shift toward binocular, patient-customized refractive planning. Early clinical reports suggest it can deliver a continuous range of vision without significantly compromising visual quality, though careful patient counseling and case selection are essential. Future directions include the integration of advanced diagnostics, artificial intelligence-driven IOL planning tools, and adaptive optics simulations to refine this personalized approach further. The promise of FOB is to improve cataract surgery outcomes by achieving an optimal balance: one that provides each patient with excellent visual quality and functional vision across distances, tailored to their lifestyle and expectations. Full article

Tongue cancer, the most aggressive subtype of oral cancer, presents critical challenges due to the limited number of specialists available and the time-consuming nature of conventional histopathological diagnosis. To address these issues, we developed an intelligent diagnostic system integrating Mueller matrix microscopy with deep learning to enhance diagnostic accuracy and efficiency. Through Mueller matrix polar decomposition and transformation, micro-polarization feature parameter images were extracted from tongue cancer tissues, and purity parameter images were generated by calculating the purity of the Mueller matrices. A multi-stage feature dataset of Mueller matrix parameter images was constructed using histopathological samples of tongue cancer tissues with varying stages. Based on this dataset, the clinical potential of Mueller matrix microscopy was preliminarily validated for histopathological diagnosis of tongue cancer. Four mainstream medical image classification networks—AlexNet, ResNet50, DenseNet121 and VGGNet16—were employed to quantitatively evaluate the classification performance for tongue cancer stages. DenseNet121 achieved the highest classification accuracy of 98.48%, demonstrating its potential as a robust framework for rapid and accurate intelligent diagnosis of tongue cancer. Full article

Terahertz (THz) frequencies, spanning from 0.1 to 1 THz, are poised to play a pivotal role in the development of future 6G wireless communication systems. These systems aim to utilize photonic technologies to enable ultra-high data rates—on the order of terabits per second—while maintaining low latency and high efficiency. In this work, we present a novel photonic method for generating sub-THz vector signals within the THz band, employing a semiconductor optical amplifier (SOA) and phase modulator (PM) to create an optical frequency comb, combined with in-phase and quadrature (IQ) modulation techniques. We demonstrate, both through simulation and experimental setup, the generation and successful transmission of a 0.1 THz vector. The process involves driving the PM with a 12.5 GHz radio frequency signal to produce the optical comb; then, heterodyne beating in a uni-traveling carrier photodiode (UTC-PD) generates the 0.1 THz radio frequency signal. This signal is transmitted over distances of up to 30 km using single-mode fiber. The resulting 0.1 THz electrical vector signal, modulated with quadrature phase shift keying (QPSK), achieves a bit error ratio (BER) below the hard-decision forward error correction (HD-FEC) threshold of ${3.8 \times 10}^{-3}$. To the best of our knowledge, this is the first experimental demonstration of a 0.1 THz photonic vector THz wave based on an SOA and a simple PM-driven optical frequency comb. Full article

Chemically strengthened glass is widely used for its remarkable fracture strength, mechanical performance, and scratch resistance. Assessing its hardness is crucial to evaluating improvements from chemical tempering. However, conventional methods like Vickers hardness tests are destructive, altering the sample surface. This study presents a novel, rapid, and nondestructive testing (NDT) approach by correlating the nonlinear refractive index (n₂) with surface hardness. Using ultrafast laser pulses, we measured the n₂ cross-section via the nonlinear ellipse rotation (NER) signal in Gorilla^®-type glass subjected to ion exchange (Na⁺ by K⁺). A microscope objective lens provided a penetration resolution of ≈5.5 μm, enabling a localized NER signal analysis. We demonstrate a correlation between the NER signal and hardness, offering a promising pathway for advanced, noninvasive characterization. This approach provides a reliable alternative to traditional destructive techniques, with potential applications in industrial quality control and material science research. Full article

Yb_xEr_yZnO thin films with a low concentration (x = 5%, y = 0, 1, 3%) were made on glass substrates using the spray pyrolysis method. The films were characterized through the use of specific techniques to investigate their structural, optical, and electrical properties. The XRD structural analysis of the films revealed that they are polycrystalline with a hexagonal wurtzite structure and a preferential orientation in the (002) direction. The optical characterization of the co-doped layers in the range of 200 to 800 nm revealed that co-doping had a significant impact on the values of transmission. A well-defined peak in the infrared domain centered around 980 nm was observed in photoluminescence measurements. This peak signifies the transition between the electronic levels ²F_5/2 (ground state) and ²F_7/2 (excited state), proving that photons are efficiently transferred between the ZnO matrix and the Yb³⁺ ion. All layers exhibited n-type conduction and an electrical resistivity decrease to 6.0 × 10⁻² Ω cm according to Hall effect measurements at room temperature. Full article

Wavefront sensing is an essential technique in optical imaging, adaptive optics, and atmospheric turbulence correction. Traditional wavefront reconstruction methods, including the Gerchberg–Saxton (GS) algorithm and phase diversity (PD) techniques, are often limited by issues such as low inversion accuracy, slow convergence, and the presence of multiple possible solutions. Recent developments in deep learning have led to new methods, although conventional CNN-based models still face challenges in effectively capturing global context. To overcome these limitations, we propose a Transformer-based single-shot wavefront sensing method, which directly reconstructs wavefront aberrations from focal plane intensity images. Our model integrates a Normalization-based Attention Module (NAM) into the CoAtNet architecture, which strengthens feature extraction and leads to more accurate wavefront characterization. Experimental results in both simulated and real-world conditions indicate that our method achieves a 4.5% reduction in normalized wavefront error (NWE) compared to ResNet34, suggesting improved performance over conventional deep learning models. Additionally, by leveraging Walsh function modulation, our approach resolves the multiple-solution problem inherent in phase retrieval techniques. The proposed model achieves high accuracy, fast convergence, and simplicity in implementation, making it a promising solution for wavefront sensing applications. Full article

We present an empirical model for the cross-section of low concentration acetone gas in the range of 1671.5–1675 nm that encompasses the absorption band of the methyl stretch overtone. This model is experimentally validated with cavity ring-down spectroscopy (CRDS) measurements performed with a calibration gas and its diluted mixtures with breath samples. Particular attention is paid to accurate wavelength measurements with an interferometric wavemeter. The theoretical framework for analysis of gas mixtures with several absorbing species is presented. We show that the proposed empirical model can be used to accurately determine the concentration of acetone vapor in human breath samples. The comparison of the acetone absorption cross-section with previous results is also presented. Full article

In this paper, a high-linear-sensitivity fiber curvature sensor based on the sphere-shaped misaligned structure (SSMS) with few-mode fiber (FMF) and single-mode fiber (SMF) was proposed and demonstrated. A spherical structure was prepared at one end of a few-mode fiber, which could effectively excite higher-order modes and generate interference in the misaligned cascade. When external environmental parameters changed, the resonance peaks formed by intermodal interference were displaced, and the shifts generated by different resonant peaks were also different. The experimental results show that the maximum curvature sensitivity was −2.220 nm/m⁻¹, and the linear fitting coefficient reached up to 0.991, which is an extremely high sensitivity among wavelength-modulated curvature sensors. Meanwhile, the strain sensitivity of the sensor was as low as 7.99 pm/μ$\overline{\mathsf{\epsilon }}$, and the temperature sensitivity was 3.958 pm/°C, which is a low temperature sensitivity and low strain sensitivity, and solves the cross-sensitivity problem. With advantages of simple manufacture, low cost, and favorable stability, the sensor is expected to be one of the best candidate instruments for measuring curvature and inclination. Full article

Pork adulteration detection in beef is important due to health, economic, and religious concerns. This study explored the use of a Shortwave Near Infrared–Hyperspectral Imaging (SWNIR–HSI) system which captured spectral data across 894–2504 nm to detect adulteration of pork in beef. In this study, minced pork in various concentrations ranging from 0–50% (w/w) were added to pure minced beef. Spectra obtained from the SWNIR–HSI were used to develop a partial least square regression (PLSR) model. The study compared the PLSR results between full wavelengths (variables) and selected wavelengths obtained via the variable importance in projection (VIP) method. The best results from the full-wavelength PLSR model yielded a prediction accuracy (R²P) of 0.940 and a standard error of prediction (SEP) of 4.633%, while using VIP-selected wavelengths improved performance, with R²P of 0.955 and SEP of 3.811%. The study demonstrates the potency of SWNIR–HIS, particularly with selected wavelengths, as an effective and nondestructive tool for accurately predicting pork adulteration levels in beef. Full article

This study explores electrochemical etching to form porous silicon (PS), which has diverse biomedical and energy applications. Our objective is to gain new insights and drive significant scientific and technological advancements. Specifically, we study the effect of electrochemical etching of P-type silicon using laser irradiation in a hydrofluoric acid (HF) solution. The formation of the nanoscale PS structure can be successfully controlled by incorporating laser irradiation into the electrochemical etching process. The wavelength and power of the laser influence the formation of nanoporous silicon (NPS) on the surface during the electrochemical etching process. The luminous flux is monitored with the help of a customized integrating sphere system and an LED-based excitation source to find the light flux values distributed across the P-type nanolayer PS wafers. Analysis of the NPS and luminescence characteristics shows that the laser bandwidth controls the band gap energy absorption (BEA) phenomenon during the electrothermal reaction. It is demonstrated that formation of the NPS layer can be controlled in this combined laser irradiation and electrochemical etching technique by adjusting the range of the laser wavelength. This also allows for further precise control of the numerical trend of the luminous flux. Full article

The World Health Organization (WHO) cancer agency predicts that more than 35 million cases of cancer will be experienced in 2050, a 77% increase over the 2022 estimate. Currently, the main cancers diagnosed are breast, lung, and colorectal. There is no standardized tool for cancer diagnoses; initially, clinical procedures are guided by the patient symptoms and usually involve biochemical blood tests, imaging, and biopsy. Label-free non-linear optical approaches are promising tools for tumor imaging, due to their inherent non-invasive biosafe contrast mechanisms and the ability to monitor collagen-related disorders, and biochemical and metabolic changes during cancer progression. In this review, the main non-linear microscopy techniques are discussed, according to three main contrast mechanisms: biochemical, metabolic, and structural imaging. Full article

We present an optical metasurface with symmetrical individual elements sustaining Fano resonances with high Q-factors. This study combines plane-wave illumination and modal analysis to investigate the resonant behavior that results in a suppression of the forward scattering, and we investigate the role of the lattice constant on the excited multipoles and on the spectral position and Q-factor of the Fano resonances, revealing the nonlocal nature of the resonances. The results show that the intrinsic losses play a crucial role in modulating the resonance amplitude in specific conditions and that the optical behavior of the device is extremely sensitive to the pitch of the metasurface. The findings highlight the importance of near-neighbor interactions to achieve high Q resonances and offer an important tool for the design of spectrally tunable metasurfaces using simple geometries. Full article

Plasmonic arrays are grating-like structures able to couple an incoming electromagnetic field into either localized or propagating surface plasmonic modes. A triangular array of elliptical holes in a gold layer were realized resorting to displacement Talbot lithography. Scanning electron microscopy was used to evaluate the geometrical features and finite time domain simulations were performed to verify the consistency of the design. The optical response was characterized by angle-resolved reflectance and transmittance measurements. The results demonstrate the good quality and uniformity of the array. Furthermore, the study on the dependence of the optical response on both the hexagonal lattice and the elliptical hole-defined symmetry properties was conducted allowing the distinction of their effects on both the localized and propagating plasmonic modes. The results indicate that the localized component of the plasmonic modes is mainly affected by the elliptical shape, while the propagating part is influenced by the hexagonal lattice symmetry. Full article

The selection of an affordable method to fabricate plasmonic metasurfaces needs to guarantee complex control over both tunability and reproducibility of their spectral and morphological properties, making plasmonic metasurfaces suitable for integration into different sensing devices. Displacement Talbot lithography could be a valid solution thanks to the limited fabrication steps required, also providing the highly desired industrial scalability. Fabricated plasmonic metasurfaces are represented by a gold nanohole array on a glass substrate based on a triangular pattern. Scanning electron microscopy measurements have been recorded, showing the consistency of the surface features with the optimized design parameters. Reflectance and transmittance measurements have also been carried out to test the reliability and standardization of the metasurface’s optical response. Furthermore, these plasmonic metasurfaces have also been successfully tested for probing refractive index variations in a microfluidic system, paving the way for their use in sensitive, real-time, label-free, and multiplexing detection of bio-molecular events. Full article

Artificial intelligence paradigms hold significant potential to advance nanophotonics. This study presents a novel approach to designing a plasmonic absorber using an artificial neural network as a surrogate model in conjunction with a genetic algorithm. The methodology involved numerical simulations of multilayered metal–dielectric plasmonic structures to establish a dataset for training an artificial neural network (ANN). The results demonstrate the proficiency of the trained ANN in predicting reflectance spectra and its ability to generalize intricate relationships between desired performance and geometric configurations, with values of correlation higher than 98% in comparison with ground-truth electromagnetic simulations. Furthermore, the ANN was employed as a surrogate model in a genetic algorithm (GA) loop to achieve target optical behaviors. The proposed methodology provides a powerful means of inverse designing multilayered metal–dielectric devices tailored for visible band wavelength filtering. This research demonstrates that the integration of AI-driven approaches in nanophotonics leads to efficient and effective design strategies. Full article

We simulate ultrafast electronic transitions in an atom and corresponding absorption line changes with a numerical, few-level model, similar to previous work. In addition, a convolutional neural network (CNN) is employed for the first time to predict electronic state populations based on the simulated modifications of the absorption lines. We utilize a two-level and four-level system, as well as a variety of laser-pulse peak intensities and detunings, to account for different common scenarios of light–matter interaction. As a first step towards the use of CNNs for experimental absorption data in the future, we apply two different noise levels to the simulated input absorption data. Full article

Image fusion is an effective and efficient way to express the feature information of an infrared image and abundant detailed information of a visible image in a single fused image. However, obtaining a fused result with good visual effect, while preserving and inheriting those characteristic details, seems a challenging problem. In this paper, by combining a multi-level smoothing filter and regional weight analysis, a dual-band image fusion approach is proposed. Firstly, a series of dual-band image layers with different details are obtained using smoothing results. With different parameters in a bilateral filter, different smoothed results are achieved at different levels. Secondly, regional weight maps are generated for each image layer, and then we fuse the dual-band image layers with their corresponding regional weight map. Finally, by imposing proper weights, those fused image layers are synthetized. Through comparison with seven excellent fusion methods, both subjective and objective evaluations for the experimental results indicate that the proposed approach can produce the best fused image, which has the best visual effect with good contrast, and those small details are preserved and highlighted, too. In particular, for the image pairs with a size of 640 × 480, the algorithm could provide a good visual effect result within 2.86 s, and the result has almost the best objective metrics. Full article

The feasibility of introducing optical nonlinearity in poly-dimethyl siloxane (PDMS) using organic solvent swelling was investigated. The third-order nonlinear refraction and absorption properties of the individual materials, as well as the PDMS/solvent compounds after swelling were characterized. The well-established Z-scan technique served as characterization method for the nonlinear properties under picosecond pulsed laser excitation at a 532 nm wavelength. These experiments included investigations on the organic solvents nitrobenzene, 2,6-lutidine, and toluene, which showed inherent optical nonlinearity. We showed that nitrobenzene, one of the most well-known nonlinear optical materials, has proven suboptimal in this context due to its limited swelling effect in PDMS and comparatively high (non)linear absorption, resulting in undesirable thermal effects and potential photo-induced damage in the composite material. Toluene and 2,6-lutidine not only exhibited lower absorption compared to nitrobenzene but also show a more pronounced swelling effect in PDMS. The incorporation of toluene caused a weight change of up to 116% of PDMS, resulting in substantial nonlinear optical effects, reflected in the nonlinear refractive index of the PDMS/toluene composite $n_2=3.1\times {10}^{-15}{\mathrm{c}\mathrm{m}}^2/\mathrm{W}$. Full article

DSPI (Digital Speckle Pattern Interferometry) is a non-destructive optical measurement technique that obtains phase information of an object through phase unwrapping. Traditional phase unwrapping algorithms depend on the quality of the images, which demands preprocessing such as filtering and denoising. Moreover, the unwrapping time is highly influenced by the size of the images. In this study, we proposed a new deep learning-based phase unwrapping algorithm combining the residual network and U-Net network. Additionally, we incorporated an improved SSIM function as the loss function based on camera characteristics. The experimental results demonstrated that the proposed method achieved higher quality in highly noisy phase unwrapping maps compared to traditional algorithms, with SSIM values consistently above 0.98. In addition, we applied image stitching to the network to process maps of various sizes and the unwrapping time remained around 1 s even for larger images. In conclusion, our proposed network is able to achieve efficient and accurate phase unwrapping. Full article

Laser-induced periodic surface structures (LIPSS) have gained significant attention due to their ability to modify the surface morphology of materials at the micro-nanoscale and show great promise for surface functionalization applications. In this study, we specifically investigate the formation of LIPSS in silicon substrates and explore their impact on surface-enhanced Raman spectroscopy (SERS) applications. This study reveals a stepwise progression of LIPSS formation in silicon, involving three distinct stages of LIPSS: (1) integrated low-spatial-frequency LIPSS (LSFL) and high-spatial-frequency LIPSS (HSFL), (2) principally LSFL and, (3) LSFL at the edge of the irradiated spot, elucidating the complex interplay between laser fluence, pulse number, and resulting surface morphology. Furthermore, from an application standpoint, these high-quality multi-scale periodic patterns lead to the next step of texturing the entire silicon surface with homogeneous LIPSS for SERS application. The potential of LIPSS-fabricated silicon substrates for enhancing SERS performance is investigated using thiophenol as a test molecule. The results indicate that the Au-coated combination of LSFL and HSFL substrates showcased the highest enhancement factor (EF) of $1.38\times {10}^6$. This pronounced enhancement is attributed to the synergistic effects of localized surface plasmon resonance (LSPR) and surface plasmon polaritons (SPPs), intricately linked to HSFL and LSFL characteristics. These findings contribute to our understanding of LIPSS formation in silicon and their applications in surface functionalization and SERS, paving the way for sensing platforms. Full article

Advanced Raman spectroscopy (RS) systems have gained new interest in the field of medicine as an emerging tool for in vivo tissue discrimination. The coupling of RS with artificial intelligence (AI) algorithms has given a boost to RS to analyze spectral data in real time with high specificity and sensitivity. However, limitations are still encountered due to the large amount of clinical data which are required for the pre-training process of AI algorithms. In this study, human healthy and cancerous colon specimens were surgically resected from different sites of the ascending colon and analyzed by RS. Two transfer learning models, the one-dimensional convolutional neural network (1D-CNN) and the 1D–ResNet transfer learning (1D-ResNet) network, were developed and evaluated using a Raman open database for the pre-training process which consisted of spectra of pathogen bacteria. According to the results, both models achieved high accuracy of 88% for healthy/cancerous tissue discrimination by overcoming the limitation of the collection of a large number of spectra for the pre-training process. This gives a boost to RS as an adjuvant tool for real-time biopsy and surgery guidance. Full article

Photodissolution is a process that is well known for its ability to cause inclusion of silver into the matrix of a chalcogenide layer, changing its optical properties. In this paper, using e-beam deposition, we developed Ag (74 nm)/As₂S₃ (355 nm) bilayers and characterized the photodissolution kinetics when exposed to actinic radiation. We showed that local complete silver photodissolution at the micron scale can be achieved. Based on this result, we then developed amplitude-based computer-generated holograms using direct laser writing. CW lasers with beam shaping and short pulse lasers with beam scanning were both implemented. Elements with 8.5 µm and <1 µm spatial resolution and close to theoretical intensity distribution, respectively, were successfully demonstrated. Full article

Over the past few years, tremendous research concerning the possibilities of gold nanoparticles in medicine has been conducted. Gold nanoparticles (AuNPs) are considered to be unique nanostructures due to their extraordinary chemical and physical properties. This review article aims to bring into light the potential applications of gold nanoparticles for diagnostic purposes in ophthalmology. More specifically, attention will be drawn to the utilization of AuNPs as contrast agents (CAs) in optical coherence tomography (OCT) and photoacoustic imaging (PAI), which are two novel imaging modalities for the visualization of the eye. None of these techniques requires the use of an imaging adjuvant to function; however, the addition of a contrast agent has been proposed for image improvement, and AuNPs are attractive candidates for this purpose. The in vitro, ex vivo, and in vivo studies investigating and supporting this concept will be presented thoroughly to elucidate whether AuNPs are eligible for imaging enhancement owing to their optical characteristics. Full article

Gas remote detection is useful for early warning of gas leakage and toxic chemicals. Optical gas imaging (OGI) built with an uncooled infrared camera is superior to cooled detectors in terms of cost. Current mainstream OGI technologies fall short in their detection of gases at ambient temperature and their ability to classify multiple gases. A multi-spectral uncooled imager is developed to try to solve these problems, which is constructed from a commercial uncooled thermal camera and wide band filters. To solve filter self-radiation and unevenness, a correction method is devised, with an ambient temperature blackbody placed in front and subtracted from the measured image. Based on waveband cutoffs, filters are classified into target-sensitive filters and background filters. Multi-spectra are simulated according to wide band filter transmittance, which can be used in gas classification. A sulfur hexafluoride (SF6) experiment is conducted outdoors at a distance of 10 m. An SVM model is trained to classify gas release in real time. Detection with a cold sky background is improved with the aid of data cube differences in a time sequence. The SF6 outdoor experiment concluded with preliminary effective results of ambient temperature gas remote detection. Full article

Previous research has shown that phenomenological approaches in early optics education might be superior to traditional model-based instruction based on the light ray realm with regards to fostering students’ conceptual understanding of basic optics topics. However, it remains open to date which learning difficulties students encounter when being introduced to optics following a phenomenological approach—in particular, in comparison to the learning difficulties that are widespread among students introduced to optics via traditional model-based instruction. With this article, we contribute to closing this gap: We report the results of a quasi-experimental field study with $N=189$ secondary school students. We used ten items adapted from the literature in a pre-posttest design for an in-depth exploration of the conceptions of introductory optics topics acquired by $N=89$ students introduced to optics following a phenomenological teaching-learning sequence and compare these students’ conceptions to the ones acquired by $N=100$ peers who participated in traditional model-based instruction covering the same content topics. The results of this study substantiate earlier findings according to which phenomenological teaching might be a fruitful endeavour for early optics education, in particular, when it comes to teaching and learning about image formation by converging lenses. Full article

Quantum state tomography (QST) refers to any method that allows one to reconstruct the accurate representation of a quantum system based on data obtainable from an experiment. In this paper, we concentrate on theoretical methods of quantum tomography, but some significant experimental results are also presented. Due to a considerable body of literature and intensive ongoing research activity in the field of QST, this overview is restricted to presenting selected ideas, methods, and results. First, we discuss tomography of pure states by distinguishing two aspects—complex vector reconstruction and wavefunction measurement. Then, we move on to the Wigner function reconstruction. Finally, the core section of the article is devoted to the stroboscopic tomography, which provides the optimal criteria for state recovery by including the dynamics in the scheme. Throughout the paper, we pay particular attention to photonic tomography, since multiple protocols in quantum optics require well-defined states of light. Full article

Tungsten (W) is the material selected for the divertor exhaust of the international nuclear fusion experiment ITER. In this harsh environment, the interactions of heat loads and ion fluxes with W can induce temporary or permanent evolution in the optical properties. Poor knowledge of such evolution during a plasma operation can lead to errors in temperature measurements performed by optical diagnostics. Therefore, it is of fundamental importance to characterize possible changes in W optical properties. In this work, we studied the role of morphology and temperature on the optical response of W. The reflectivities of five W samples with different roughness values (20–100 nm) were measured during laser annealing (25–800 °C) in the visible and near-infrared domains (500–1100 nm). We observed an increase in reflectivity after annealing and we demonstrated that it was due to a change in the chemical composition of the surface, in particular a reduction in the amount of native oxide. Moreover, we show that roughness does not sensibly vary in the investigated temperature range. By highlighting the role played by roughness and surface impurities (e.g., oxide), we provide insight in how W optical properties can evolve in tokamaks where high ion fluxes, heat loads, and impurities can induce the evolution of both the morphology and surface composition of W. Full article

Temperature is one of the most relevant physical quantities that affects almost all processes in nature. However, the realization of accurate temperature standards using current temperature references, like the triple point of water, is difficult due to the requirements on material purity and stability of the environment. In addition, in harsh environments, current temperature sensors with electrical readout, like platinum resistors, are difficult to implement, urging the development of optical temperature sensors. In 2018, the European consortium Photoquant, consisting of metrological institutes and academic partners, started investigating new temperature standards for self-calibrated, embedded optomechanical sensor applications, as well as optimised high resolution and high reliability photonic sensors, to measure temperature at the nano and meso-scales and as a possible replacement for the standard platinum resistant thermometers. This article presents an overview of the results obtained with sensor prototypes that exploit photonic and optomechanical techniques for sensing temperatures over a large temperature range (5 K to 300 K). Different concepts are demonstrated, including ring resonators, ladder-like resonators and suspended membrane optomechanical thermometers, highlighting initial performance and challenges, like self-heating that need to be overcome to realize photonic and optomechanical thermometry applications. Full article

Correlation plenoptic imaging (CPI) is an optical imaging technique based on intensity correlation measurement, which enables detecting, within fundamental physical limits, both the spatial distribution and the direction of light in a scene. This provides the possibility to perform tasks such as three-dimensional reconstruction and refocusing of different planes. Compared with standard plenoptic imaging devices, based on direct intensity measurement, CPI overcomes the problem of the strong trade-off between spatial and directional resolution. Here, we study the resolution limit in a recent development of the technique, called correlation plenoptic imaging between arbitrary planes (CPI-AP). The analysis, based on Gaussian test objects, highlights the main properties of the technique, as compared with standard imaging, and provides an analytical guideline to identify the limits at which an object can be considered resolved. Full article