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Quantum key distribution (QKD) is one quantum technology that can provide secure encryption keys for data transmission. The secret key rate (SKR) is a core performance indicator in QKD, which directly determines the transmission rate of enciphered data. Here, for the first time, we demonstrate a high-key-rate Gaussian-modulated continuous-variable QKD (CV-QKD) using telecom optical components. The framework of CV-QKD over these components is constructed. Specifically, the high-rate low-noise Gaussian modulation of coherent states is realized by a classical optical IQ modulator. High-baud low-intensity quantum signals are received by an integrated coherent receiver under the shot-noise limit. A series of digital signal processing algorithms are proposed to achieve accurate signal recovery and key distillation. The system can yield a high asymptotic SKR of 10.37 Mbps within 20 km standard telecom fiber, and the secure distance can exceed 100 km. This result confirms the feasibility of CV-QKD with state-of-the-art performance using telecom optical components. Besides, due to the ease of integrating these discrete components, it provides a high-performance and miniaturized QKD solution for the metropolitan quantum network.

The EPICS State Notation Language (SNL) and associated sequencer can be used to design a sequence of events which are defined by states. This state function ability has prompted us to investigate application of SNL to automate beamline tasks starting with a simpler process of automating monochromator warming. Further extending the idea to implement beam delivery. Our aim here is to drive the optical components of the beamline in a learned manner, to deliver beam from source to sample position.

The challenge of maintaining consistent quality in injection molding is critical, yet conducting a comprehensive inspection is both costly and time consuming. Leveraging artificial intelligence, this study proposed using machine learning—specifically multilayer perception (MLP) models—to predict the quality of injection-molded parts. The accuracy of this approach largely relies on hyperparameter tuning, a process that can be cumbersome and suboptimal if performed through trial and error. The Taguchi method has the advantages of robustness, efficiency, and simplicity, and is a widely used robust optimization tool. However, this method assumes a linear relationship between factors, which limits the processing of complex systems where interactions between factors are nonlinear. Furthermore, the Taguchi method is sensitive to initial assumptions about factors and their levels, and the results may not reflect the true behavior of the system. To address this, a two-stage design-of-experiments method was devised that systematically identifies the optimal hyperparameter settings, including the maximum number of epochs, learning rate, momentum, activation function, minimum batch size, and numbers of hidden layers and nodes. The method is executed in two stages: (1) an L 12 (2 1  × 3 5 ) orthogonal array is used to identify the primary factors affecting model accuracy and (2) an L 8 (2 3 ) full-factorial experiment is conducted discover the combinations that yield the highest performance. Two experimental case studies, integrated circuit (IC) tray width prediction and optical component weight prediction, were used to validate the proposed method. The results revealed that the best hyperparameter settings resulted in validation and test accuracy of 96.83% and 95.30%, respectively, for IC tray width prediction. The average root-mean-square errors are 0.019 and 0.022 in model validation and test, respectively, for optical component weight prediction, with short computational time. The proposed method demonstrates how the systematic optimization of hyperparameters for MLP model can enhance the efficiency and stability of model training and can be used to advance quality control in the field of injection molding.

Advancements in astronomical telescopes and cutting-edge technologies, including deep ultraviolet (DUV) and extreme ultraviolet (EUV) lithography, have escalated demands and imposed stringent surface quality requirements on optical system components. Achieving near-ideal optical components requires ultra-smooth surfaces with sub-nanometer roughness, no sub-surface damage, minimal surface defects, low residual stresses, and intact lattice integrity. This necessity has driven the rapid development and diversification of ultra-smooth surface fabrication technologies. This paper summarizes recent advances in ultra-smooth surface processing technologies, categorized by their material removal mechanisms. A subsequent comparative analysis evaluates the roughness and polishing characteristics of ultra-smooth surfaces processed on various materials, including fused silica, monocrystalline silicon, silicon carbide, and sapphire. To maximize each process’s advantages and achieve higher-quality surfaces, the paper discusses tailored processing methods and iterations for different materials. Finally, the paper anticipates future development trends in response to current challenges in ultra-smooth surface processing technology, providing a systematic reference for the study of the production of large-sized freeform surfaces.

The uniformity of the machining results in the rough polishing of optical components that determines the length of the subsequent fine polishing cycle. In this paper, full-calibre polishing of large-calibre flat optical components using the motion mode of the ring pendulum double-sided polisher is studied. The processing motion model of the ring pendulum-type double-sided polisher is built to predict the processing results. Based on the model predictions, the simulated machining experiment was carried out to analyze the experimental results. The processing characteristics of different-sized polishing discs are used to optimize the polishing process. Experiments show that the optimization scheme can effectively improve the uniformity of the machined surface.

We have proposed a fruitful design principle targeting a concentration ratio (CR) >1000× for a typical high concentrating photovoltaics (HCPV) system, on account of a two-concentrator system + homogenizer. The principle of a primary dual-lens concentrator unit, completely analogous basic optics seen in the superposition compound eyes, is a trend not hitherto reported for solar concentrators to our knowledge. Such a concentrator unit, consisting of two aspherical lenses, can be applied to minify the sunlight and reveal useful effects. We underline that, at this stage, the CR can be attained by two orders of magnitude simply by varying the radius ratio of such two lenses known from the optics side. The output beam is spatially minimized and nearly parallel, exactly as occurs in the superposition compound eye. In our scheme, thanks to such an array of dual-lens design, a sequence of equidistant focal points is formed. The secondary concentrator consists of a multi-reflective channel, which can collect all concentrated beams from the primary concentrator to a small area where a solar cell is placed. The secondary concentrator is located right underneath the primary concentrator. The optical characteristics are substantiated by optical simulations that confirm the applicability of thousands-fold gain in CR value, ~1100×. This, however, also reduced the uniformity of the illumination area. To regain the uniformity, we devise a fully new homogenizer, hinging on the scattering principle. A calculated optical efficiency for the entire system is ~75%. Experimentally, a prototype of such a dual-lens concentrator is implemented to evaluate the converging features. As a final note, we mention that the approach may be extended to implement an even higher CR, be it simply by taking an extra concentrator unit. With simple design of the concentrator part, which may allow the fabrication process by modeling method and large acceptant angle (0.6°), we assess its large potential as part of a general strategy to implement a highly efficient CPV system, with minimal critical elaboration steps and large flexibility.

To simplify complex optical systems, a next-generation optical component which combines a refractive element and a diffractive element is desirable. To fabricate these next-generation optical components, it is desirable to keep the focal point of the lithographic lens focused on the curved surface. Keeping the focus constant is challenging for a laser process, as well as for measuring and metrology systems. In this study, a coaxial confocal microscopic type commercialized displacement sensor was used to make it easier to fabricate the pattern required for diffractive optical elements (DOEs) on a curved surface, using direct laser lithography. The test results confirmed that a constant line width of 5 μm could be fabricated on a curved surface such as a cylinder and convex lens using the proposed auto-surface tracking system, with a position error of 1 μm. The diffraction pattern fabricated on the curved surface was analyzed for optical performance and compared with mathematical modeling.

Large-aperture optical components are of paramount importance in domains such as integrated circuits, photolithography, aerospace, and inertial confinement fusion. However, measuring their surface profiles relies predominantly on the phase-shifting approach, which involves collecting multiple interferograms and imposes stringent demands on environmental stability. These issues significantly hinder its ability to achieve real-time and dynamic high-precision measurements. Therefore, this study proposes a high-precision large-aperture single-frame interferometric surface profile measurement (LA-SFISPM) method based on deep learning and explores its capability to realize dynamic measurements with high accuracy. The interferogram is matched to the phase by training the data measured using the small aperture. The consistency of the surface features of the small and large apertures is enhanced via contrast learning and feature-distribution alignment. Hence, high-precision phase reconstruction of large-aperture optical components can be achieved without using a phase shifter. The experimental results show that for the tested mirror with Φ = 820 mm, the surface profile obtained from LA-SFISPM is subtracted point-by-point from the ground truth, resulting in a maximum single-point error of 4.56 nm. Meanwhile, the peak-to-valley (PV) value is 0.075 8 λ, and the simple repeatability of root mean square (SR-RMS) value is 0.000 25 λ, which aligns well with the measured results obtained by ZYGO. In particular, a significant reduction in the measurement time (reduced by a factor of 48) is achieved compared with that of the traditional phase-shifting method. Our proposed method provides an efficient, rapid, and accurate method for obtaining the surface profiles of optical components with different diameters without employing a phase-shifting approach, which is highly desired in large-aperture interferometric measurement systems. This is the first time that high-precision measurement of large-aperture optical components has been realized by capturing single-frame interferograms without requiring a phase shifter. We integrate deep learning algorithms with interferometry methods to simulate the interferometric process in a deep learning framework. This approach mitigates environmental noise effects on measurement accuracy, eliminates phase shifters, and enables dynamic surface profile measurements of large-aperture optical components. Compared with traditional phase-shifting methods, this approach achieves a 48-fold time reduction while improving measurement efficiency and stability. We demonstrate a highly efficient dynamic measurement method that achieves comparable accuracy without ZYGO interferometers’ ultra-stable environment requirements.

Magnetorheological finishing (MRF) of aspherical optical elements usually requires the coordination between the translational axes and the oscillating axes of the machine tool to realize the processing. For aspheric optical elements whose steepness exceeds the machining stroke of the equipment, there is still no better method to achieve high-precision and high-efficiency error convergence. To solve this problem, an MRF method combining virtual-axis technology and a spiral scanning path is proposed in this paper. Firstly, the distribution law of the magnetic induction intensity inside the polishing wheel is analyzed by simulation, the stability of the removal efficiency of the removal function within the ±7∘ angle of the normal angle of the polishing wheel is determined, and MRF is expanded from traditional single-point processing to circular arc segment processing. Secondly, the spiral scanning path is proposed for aspherical rotational symmetric optical elements, which can reduce the requirements of the number of machine tool axes and the dynamic performance of machine tools. Finally, an aspherical fused silica optical element with a curvature radius of 400 mm, K value of −1, and aperture of 100 mm is processed. The PV value of this optical element converges from 189.2 nm to 24.85 nm, and the RMS value converges from 24.85 nm to 5.74 nm. The experimental results show that the proposed combined process has the ability to modify curved optical elements and can be applied to ultra-precision machining of high-steepness optical elements.

With the widespread application of optical technology in numerous fields, the polarization performance of transmissive optical components has become increasingly crucial. The extinction ratio, an important indicator for evaluating their polarization characteristics, holds great significance for its precise detection. Aiming at the measurement of the extinction ratio of a transparent component, this study proposes a measurement method for solving the extinction ratio based on measuring the Mueller matrix of the transparent component. The purpose is to analyze the worst position of the extinction ratio of the transmissive component. The extinction ratio of the sample is obtained according to the phase retardation derived from the Stokes vector of the incident light and the Mueller matrix of the optical component, and a theoretical analysis and simulation of this method are carried out. The simulation results verify the feasibility of the theoretical derivation of this method. To further verify the accuracy of the measurement method, experimental verification is conducted. A standard transparent sample with a phase retardation of 13 nm is selected for actual measurement. The data of independent experiments on the transparent sample under different powers are analyzed, and the extinction ratio of the transparent sample is further obtained. When using this method, the relative error is less than 2%, indicating good accuracy.