In light of the Bruijn method, a new analytical approach for predicting the field enhancement's dependence on critical geometric SRR parameters was formulated and numerically confirmed. While a typical LC resonance is commonplace, the amplified field at the coupling resonance demonstrates a high-quality waveguide mode within the circular cavity, thus setting the stage for the direct transmission and detection of intensified THz signals in prospective communication systems.

Two-dimensional (2D) optical elements, phase-gradient metasurfaces, manipulate incident electromagnetic waves by locally and spatially varying the phase. By providing ultrathin alternatives, metasurfaces hold the key to revolutionizing photonics, enabling the replacement of common optical elements like bulky refractive optics, waveplates, polarizers, and axicons. Nevertheless, the creation of cutting-edge metasurfaces frequently involves a series of time-consuming, costly, and potentially dangerous processing stages. Our research group has pioneered a facile one-step UV-curable resin printing technique for the fabrication of phase-gradient metasurfaces, thereby surpassing the limitations inherent in conventional methods. This method dramatically lowers the processing time and cost, and concurrently removes all safety hazards. To demonstrate the method's viability, a swift replication of high-performance metalenses, utilizing the Pancharatnam-Berry phase gradient principle within the visible light spectrum, unequivocally highlights their advantages.

The paper proposes a freeform reflector radiometric calibration light source system that leverages the beam shaping attributes of the freeform surface to refine the accuracy of in-orbit radiometric calibration for the Chinese Space-based Radiometric Benchmark (CSRB) reference payload's reflected solar band and curtail resource consumption. Using Chebyshev points to discretize the initial structure, a design method was formulated and applied to the freeform surface, the solution of which was subsequently obtained. The practicality of this method was subsequently substantiated by optical simulations. The freeform reflector's machined surface, after testing, showed a surface roughness root mean square (RMS) of 0.061 mm, highlighting the satisfactory continuity of the manufactured surface. The optical characteristics of the calibration light source system were quantified, revealing irradiance and radiance uniformity exceeding 98% within the 100mm x 100mm illumination area on the target plane. A freeform reflector calibration light source system for onboard payload calibration of the radiometric benchmark exhibits large area, high uniformity, and light weight, thereby contributing to improved measurement precision of spectral radiance within the reflected solar band.

Experimental results are presented for frequency down-conversion through the four-wave mixing (FWM) process, within a cold, 85Rb atomic ensemble, with a diamond-level configuration. An atomic cloud, featuring an optical depth (OD) of 190, is prepared for the purpose of achieving a high-efficiency frequency conversion. Within the near C-band range, we convert an attenuated signal pulse field at 795 nm, reduced to a single-photon level, into telecom light at 15293 nm, achieving a frequency-conversion efficiency of up to 32%. BU-4061T mw We determine that the OD is a substantial element in determining conversion efficiency, and improvement in the OD could lead to efficiencies exceeding 32%. In addition, the signal-to-noise ratio of the observed telecom field is greater than 10, and the mean signal count exceeds 2. The incorporation of quantum memories based on a cold 85Rb ensemble at 795 nm into our work could enable the development of long-distance quantum networking capabilities.

Computer vision faces a significant challenge in parsing RGB-D indoor scenes. Despite relying on manually extracted features, conventional scene-parsing methods have proven insufficient for the analysis of indoor scenes, which are both unorganized and intricate. This research proposes a feature-adaptive selection and fusion lightweight network (FASFLNet), designed for both accuracy and efficiency in parsing RGB-D indoor scenes. The FASFLNet, in its proposed form, uses a lightweight MobileNetV2 classification network to underpin its feature extraction process. FASFLNet's backbone, while lightweight, ensures both high efficiency and strong feature extraction performance. Spatial information from depth images—specifically the shape and scale of objects—is used in FASFLNet as additional data for the adaptive fusion of RGB and depth features. In the decoding phase, the features from different layers are integrated, starting from topmost to bottommost layers, and merged at various layers for the final pixel-level classification, demonstrating a similar effect to the hierarchical supervision of a pyramid. The proposed FASFLNet model's performance, as assessed by experiments on the NYU V2 and SUN RGB-D datasets, significantly surpasses existing state-of-the-art models in terms of both efficiency and accuracy.

The significant demand for creating microresonators possessing precise optical properties has instigated diverse methodologies to refine geometries, mode profiles, nonlinearities, and dispersion characteristics. In various applications, the dispersion inside such resonators balances their optical nonlinearities, consequently modifying the optical dynamics within the cavity. Our paper demonstrates a machine learning (ML) algorithm's ability to ascertain the geometry of microresonators, using their dispersion profiles as input. Finite element simulations produced a 460-sample training dataset that enabled the subsequent experimental verification of the model, utilizing integrated silicon nitride microresonators. Evaluating two machine learning algorithms with optimized hyperparameters, Random Forest exhibited superior performance. BU-4061T mw Averaged across the simulated data, the error is well under 15%.

The accuracy of approaches for estimating spectral reflectance is strongly correlated with the number, spatial coverage, and fidelity of representative samples within the training dataset. By fine-tuning the spectral characteristics of light sources, we propose a method for artificial dataset expansion, employing only a small set of actual training examples. With our expanded color samples, the reflectance estimation process was subsequently applied to common datasets such as IES, Munsell, Macbeth, and Leeds. Finally, a study is conducted to determine the effect of differing augmented color sample numbers. The results obtained through our proposed method highlight the ability to artificially augment color samples from the CCSG 140 set, reaching a considerable 13791, and potentially an even greater number. Compared to the benchmark CCSG datasets, augmented color samples show significantly enhanced reflectance estimation performance across all tested datasets (IES, Munsell, Macbeth, Leeds, and a real-scene hyperspectral reflectance database). The proposed dataset augmentation method proves to be a practical solution for enhancing the performance of reflectance estimation.

Robust optical entanglement within cavity optomagnonics is achieved through a scheme where two optical whispering gallery modes (WGMs) engage with a magnon mode within a yttrium iron garnet (YIG) sphere. Beam-splitter-like and two-mode squeezing magnon-photon interactions are simultaneously achievable when external fields act upon the two optical WGMs. Through their coupling with magnons, the entanglement of the two optical modes is established. The destructive quantum interference of bright modes within the interface effectively eliminates the consequences of the initial thermal populations of magnons. Subsequently, the Bogoliubov dark mode's activation proves effective in protecting optical entanglement from thermal heating. As a result, the generated optical entanglement is robust against thermal noise, thereby freeing us from the strict requirement of cooling the magnon mode. In the study of magnon-based quantum information processing, our scheme may find significant use.

Multiple axial reflections of a parallel light beam within a capillary cavity are a highly effective method for amplifying the optical path length and, consequently, the sensitivity of photometers. However, a non-ideal trade-off exists between the length of the optical path and the intensity of the light. For instance, a reduction in the mirror aperture size might extend the optical path via multiple axial reflections due to decreased cavity losses, yet simultaneously decrease the coupling efficiency, light intensity, and the related signal-to-noise ratio. A light beam concentrator, consisting of two lenses and an aperture mirror, was devised to boost coupling efficiency without compromising beam parallelism or increasing multiple axial reflections. The concurrent employment of an optical beam shaper and a capillary cavity produces a noteworthy amplification of the optical path (ten times the capillary length) and a high coupling efficiency (exceeding 65%). This outcome includes a fifty-fold enhancement in the coupling efficiency. A 7 cm capillary optical beam shaper photometer was developed for water detection in ethanol, exhibiting a remarkable detection limit of 125 ppm. This limit is 800 times lower than those of commercial spectrometers (using 1 cm cuvettes), and 3280 times lower than that of previous findings.

Digital fringe projection, a camera-based optical coordinate metrology technique, necessitates accurate calibration of the system's cameras for reliable results. Determining the camera model's intrinsic and distortion parameters, a procedure known as camera calibration, hinges on the location of targets, in this instance circular points, within sets of calibration images. Achieving sub-pixel accuracy in localizing these features is crucial for precise calibration, ultimately leading to high-quality measurement results. BU-4061T mw For calibrating localized features, the OpenCV library provides a common solution.