Data acquisition is performed using a combined holographic imaging and Raman spectroscopy system on six varieties of marine particles dispersed throughout a substantial volume of seawater. Convolutional and single-layer autoencoders are employed for unsupervised feature learning on the image and spectral datasets. Multimodal learned features, combined and subjected to non-linear dimensional reduction, result in a high clustering macro F1 score of 0.88, demonstrating a substantial improvement over the maximum score of 0.61 obtainable using image or spectral features alone. Particles in the ocean can be continuously monitored over extended periods by employing this method, obviating the need for collecting samples. Moreover, data from diverse sensor measurements can be used with it, requiring minimal alterations.

High-dimensional elliptic and hyperbolic umbilic caustics are generated via phase holograms, demonstrating a generalized approach enabled by angular spectral representation. The diffraction catastrophe theory, determined by the potential function dependent on state and control parameters, is used to examine the wavefronts of umbilic beams. We observe that hyperbolic umbilic beams are reducible to classical Airy beams if and only if the two control parameters are simultaneously zero, and elliptic umbilic beams demonstrate an engaging self-focusing trait. The numerical outcomes show that the beams display clear umbilics in their 3D caustic, which are conduits between the two separate portions. Their dynamical evolutions affirm the presence of substantial self-healing qualities in both. Subsequently, we showcase that hyperbolic umbilic beams exhibit a curved trajectory during their propagation. The numerical evaluation of diffraction integrals is a complex process; however, we have developed a practical solution for generating these beams, employing a phase hologram based on the angular spectrum approach. There is a significant correspondence between the simulated and experimental results. Applications for these beams, possessing compelling properties, are foreseen in burgeoning sectors such as particle manipulation and optical micromachining.

The horopter screen's curvature's effect in lessening the disparity of perception between the two eyes is a reason for its popular study; furthermore, immersive displays incorporating a horopter-curved screen are appreciated for their convincing presentation of depth and stereopsis. Despite the intent of horopter screen projection, the practical result is often a problem of inconsistent focus across the entire screen and a non-uniform level of magnification. The ability of an aberration-free warp projection to address these challenges lies in its capacity to modify the optical path, shifting it from the object plane to the image plane. Given the significant fluctuations in curvature within the horopter display, a freeform optical element is necessary to guarantee a warp projection free of aberrations. Compared to conventional fabrication methods, the hologram printer offers a speed advantage in creating custom optical devices by encoding the desired wavefront phase within the holographic material. The freeform holographic optical elements (HOEs), fabricated by our specialized hologram printer, are used in this paper to implement aberration-free warp projection onto a specified, arbitrary horopter screen. We empirically validate the effective correction of both distortion and defocus aberrations.

Optical systems are vital components in various applications, including consumer electronics, remote sensing, and biomedical imaging. Given the complexity of aberration theories and the implicit nature of design rules-of-thumb, designing optical systems has been a challenging and demanding profession; neural networks are only now entering this domain. A general, differentiable freeform ray tracing module is proposed and implemented in this work, specifically targeting off-axis, multiple-surface freeform/aspheric optical systems, which sets the stage for deep learning-based optical design. Using minimally pre-programmed knowledge, the network is trained to infer various optical systems after a single training cycle. This study's application of deep learning to freeform/aspheric optical systems results in a trained network capable of acting as a unified, effective platform for the generation, recording, and replication of optimal starting optical designs.

Photodetection employing superconductors boasts a broad spectral scope, encompassing microwaves to X-rays. In the high-energy portion of the spectrum, it enables single-photon detection. In the longer wavelength infrared, the system displays diminished detection efficiency, a consequence of the lower internal quantum efficiency and a weak optical absorption. Employing the superconducting metamaterial, we optimized light coupling efficiency, achieving near-perfect absorption at dual infrared wavelengths. Hybridization of the local surface plasmon mode within the metamaterial structure, coupled with the Fabry-Perot-like cavity mode of the metal (Nb)-dielectric (Si)-metamaterial (NbN) tri-layer, results in dual color resonances. Operating at a temperature of 8K, a value slightly below the critical temperature of 88K, this infrared detector displayed peak responsivities of 12106 V/W at 366 THz and 32106 V/W at 104 THz, respectively. The peak responsivity is considerably improved, reaching 8 and 22 times the value of the non-resonant frequency (67 THz), respectively. Our work has established a novel way to capture infrared light effectively, thereby boosting the sensitivity of superconducting photodetectors within the multispectral infrared range, with potential applications in thermal imaging, gas sensing, and other fields.

This paper proposes a method to enhance the performance of non-orthogonal multiple access (NOMA) in passive optical networks (PONs), using a 3-dimensional constellation and a 2-dimensional Inverse Fast Fourier Transform (2D-IFFT) modulator. Erlotinib in vivo In order to produce a three-dimensional non-orthogonal multiple access (3D-NOMA) signal, two types of 3D constellation mapping have been developed. Pair mapping of signals with different power levels facilitates the generation of higher-order 3D modulation signals. The successive interference cancellation (SIC) algorithm is implemented at the receiver to clear the interference generated by separate users. Erlotinib in vivo The 3D-NOMA, a departure from the standard 2D-NOMA, increases the minimum Euclidean distance (MED) of constellation points by 1548%. This improvement translates to enhanced bit error rate (BER) performance in NOMA systems. By 2dB, the peak-to-average power ratio (PAPR) of NOMA networks is lessened. The 1217 Gb/s 3D-NOMA transmission over a 25km stretch of single-mode fiber (SMF) has been experimentally verified. For a bit error rate (BER) of 3.81 x 10^-3, the sensitivity of the high-power signals in the two proposed 3D-NOMA schemes is enhanced by 0.7 dB and 1 dB, respectively, when compared with that of 2D-NOMA under the same data rate condition. The performance of low-power level signals is augmented by 03dB and 1dB. The 3D non-orthogonal multiple access (3D-NOMA) approach exhibits the potential for a greater number of users compared to 3D orthogonal frequency-division multiplexing (3D-OFDM), without any notable performance loss. The high performance of 3D-NOMA makes it a prospective method for optical access systems of the future.

A holographic three-dimensional (3D) display hinges on the indispensable nature of multi-plane reconstruction. A fundamental concern within the conventional multi-plane Gerchberg-Saxton (GS) algorithm is the cross-talk between planes, primarily stemming from the omission of interference from other planes during the amplitude update at each object plane. This paper introduces a time-multiplexing stochastic gradient descent (TM-SGD) optimization algorithm aimed at minimizing crosstalk in multi-plane reconstructions. Initially, the global optimization feature within stochastic gradient descent (SGD) was leveraged to diminish inter-plane crosstalk. In contrast, the crosstalk optimization effect is inversely proportional to the increase in object planes, owing to an imbalance between the amount of input and output information. Using the time-multiplexing approach, we improved the iterative and reconstructive processes within the multi-plane SGD algorithm to maximize the input information. Sequential refreshing of multiple sub-holograms on the spatial light modulator (SLM) is achieved through multi-loop iteration in TM-SGD. The optimization condition for holograms and object planes changes from a one-to-many mapping to a many-to-many configuration, boosting the optimization of inter-plane crosstalk. During the persistence of sight, multiple sub-holograms collaboratively reconstruct the crosstalk-free multi-plane images. The TM-SGD approach, as validated by simulations and experiments, effectively minimizes inter-plane crosstalk and improves the quality of displayed images.

Our findings demonstrate a continuous-wave (CW) coherent detection lidar (CDL) equipped for the detection of micro-Doppler (propeller) signatures and the acquisition of raster-scanned images from small unmanned aerial systems/vehicles (UAS/UAVs). The system, employing a 1550nm CW laser with a narrow linewidth, leverages cost-effective and mature fiber optic components readily found within the telecommunications industry. From a distance of 500 meters or less, the characteristic rhythms of drone propellers have been ascertained through lidar systems that use either collimated or focused laser beams. Furthermore, two-dimensional images of airborne UAVs, located up to a maximum range of 70 meters, were captured by raster scanning a focused CDL beam with a galvo-resonant mirror beamscanner. Each pixel of a raster-scan image carries data about the lidar return signal's amplitude as well as the radial velocity characteristic of the target. Erlotinib in vivo Differentiating between different types of unmanned aerial vehicles (UAVs), based on their profiles, and pinpointing payloads, is achievable through the use of raster-scanned images, which are obtained up to five times per second.