Ryepena2548

This paper presents a channel analysis method for single and double scattering events in non-line-of-sight (NLOS) ultraviolet (UV) communication systems. In general, the calculations of path loss and impulse response of such systems require Monte Carlo random number generations. However, the high computational costs of Monte Carlo methods impose severe limitations on quick reliable evaluations of system performance under complex atmospheric conditions. This paper proposes a sample-based UV channel characterization approach that improves computational performance by multiple orders of magnitude. The proposed novel approach uses fixed probability-based sampling. The method focuses only on single and double scattering events which dominate the received signal. The effects of various fog and dust aerosols are discussed under non-planar realistic conditions. The results demonstrate reliable channel characterization with significantly lower complexity using the proposed approach.Scattering generally worsens the condition of inverse problems, with the severity depending on the statistics of the refractive index gradient and contrast. Removing scattering artifacts from images has attracted much work in the literature, including recently the use of static neural networks. S. Li et al. [Optica5(7), 803 (2018)10.1364/OPTICA.5.000803] trained a convolutional neural network to reveal amplitude objects hidden by a specific diffuser; whereas Y. Li et al. [Optica5(10), 1181 (2018)10.1364/OPTICA.5.001181] were able to deal with arbitrary diffusers, as long as certain statistical criteria were met. Here, we propose a novel dynamical machine learning approach for the case of imaging phase objects through arbitrary diffusers. The motivation is to strengthen the correlation among the patterns during the training and to reveal phase objects through scattering media. We utilize the on-axis rotation of a diffuser to impart dynamics and utilize multiple speckle measurements from different angles to form a sequence of images for training. Recurrent neural networks (RNN) embedded with the dynamics filter out useful information and discard the redundancies, thus quantitative phase information in presence of strong scattering. Fingolimod supplier In other words, the RNN effectively averages out the effect of the dynamic random scattering media and learns more about the static pattern. The dynamical approach reveals transparent images behind the scattering media out of speckle correlation among adjacent measurements in a sequence. This method is also applicable to other imaging applications that involve any other spatiotemporal dynamics.This work presents a new approach for high-speed four-dimensional (3D + t) thermometry using only two high-speed cameras which are equipped with different band pass filters to capture thermal radiation signals at two narrow wavelength bands. With the help of a customized fiber bundle and a beam splitter, a total number of nine projections at each band were recorded, and the temperature distribution was evaluated by tomographic two-color pyrometry. In order to validate the effectiveness of this method, the 3D temperature distribution of a premixed steady flat flame was evaluated. The determined temperatures were compared to those of other studies, as well as to the results from inverse Abel transform and line-of-sight data. Further, the 3D temperature evolution of a weakly turbulent diffusion flame was observed at a repetition rate of 7.5 kHz. Such 4D temperature measurements are expected to be valuable in understanding turbulent combustion mechanisms especially of practical devices.We report on the design and automation of a mid-infrared, continuous wave, singly-resonant optical parametric oscillator. Hands-free controls and the implementation of a tuning algorithm allowed for hundreds of nanometers of continuous, effective-mode-hop-free tuning over the range of 2190-4000 nm. To demonstrate the applicability of this light source and algorithm to mid-IR spectroscopy, we performed a sample spectroscopy measurement in a C2H2 gas cell and compared the experimentally-measured absorption spectrum to HITRAN 2016 simulations. We found excellent agreement with simulation in both peak heights and peak centers; we also report a reduced uncertainty in peak centers compared to simulation.In this work, we utilize three parallel optical reservoir computers to model three optical dynamic systems, respectively. Here, the three laser-elements in the response laser array with both delay-time feedback and optical injection are utilized as nonlinear nodes to realize three optical chaotic reservoir computers (RCs). The nonlinear dynamics of three laser-elements in the driving laser array are predictively learned by these three parallel RCs. link2 We show that these three parallel reservoir computers can reproduce the nonlinear dynamics of the three laser-elements in the driving laser array with self-feedback. Very small training errors for their predictions can be realized by the optimization of two key parameters such as the delay-time and the interval of the virtual nodes. Moreover, these three parallel RCs to be trained will well synchronize with three chaotic laser-elements in the driving laser array, respectively, even when there are some parameter mismatches between the response laser array and the driving laser array. Our findings show that optical reservoir computing approach possibly provide a successful path for the realization of the high-quality chaotic synchronization between the driving laser and the response laser when their rate-equations imperfectly match each other.We propose and demonstrate a new kind of resonant absorber via introducing the nano-slit into a photonic film. The combination of the nano-slit cavity and the photonic waveguide provides a powerful way to manipulate the light behaviors including the spectral Q factors and the absorption efficiency. Ultra-sharp resonant absorption with the Q factors up to 579.5 is achieved, suggesting an enhancement of ∼6100% in contrast to that of the metal-dielectric flat film structure. Moreover, in comparison with the low absorption of 5.4% for the system without nano-slit, the spectral absorption is up to ∼96.6% for the nano-slit assisted photonic absorber. The high Q resonant absorption can be further manipulated via the structural parameters and the polarization state. The operation wavelengths can be tuned by the lattice constant. As the nano-slit introduced into the dielectric film, strong optical field confinement effects can be achieved by the cavity resonance via the nano-slit itself, and the guided resonant effect in the photonic waveguide cavity formed by the adjacent nano-slits. Otherwise, the photonic-plasmonic hybridization effect is simultaneously excited between the dielectric guided cavity layer and the metal substrate. link3 These findings can be extended to other photonic nano-cavity systems and pave new insights into the high Q nano-optics devices.We investigate the focusing properties of cylindrical vector beams (CVBs) generated from the combination of an array of beams, each with sub-apertures and controllable polarization. The analytical expression of the tight focusing field of the combined CVBs has been derived based on the Richard-Wolf vector diffraction integral. To obtain a desired focal spot size which includes efficient sidelobe suppression, the required parameters, such as the exit sub-aperture, numerical aperture and truncation parameter, have been studied in detail. The result shows that the combined CVB distribution has a good match with the theoretical ideal CVB distribution. However, compared with the ideal CVBs, the focal spot width produced by the combined radially polarized beams is smaller. With the increase of initial polarization rotation of sub-aperture, the focal spot width increases, and the focal shape shifts from Gaussian-like to a flat-topped distribution and then to an annular distribution. Furthermore, flexible focal field tailoring can also be realized by adjusting the initial polarization rotation of each sub-aperture. These results might provide a valuable reference for material processing, microlithography and multi-particle manipulation.In this work, we demonstrate an approach to realize geometry-invariant multi-channel coherent perfect absorbers by embedding ultrathin conductive films in zero-index media. Coherent perfect absorption can be achieved for waves incidents from an arbitrary number of input channels as long as the total width of the channels equals to a critical value that is only determined by the length and material parameters of the conductive films instead of their shapes and positions. The absorption attributes to induced currents in the conductive films by the electric fields of incidence, and the shape- and position-independent characteristics originate from the uniformly distributed electric fields inside the zero-index media. By using dielectric photonic crystals and photonic-doped zero-index media, we numerically demonstrate such an interesting transformation from zero-index media to coherent perfect absorbers. Furthermore, ultrathin coherent perfect absorbers based on zero-index media are also demonstrated in waveguides. Our work reveals a unique mechanism to change the material responses between zero-index media and coherent perfect absorbers.A novel, compact, and easy fabrication vector magnetic field sensor has been proposed and investigated. The proposed sensor consists of a U-bent single-mode fiber fixed in a magnetic-fluid-filled vessel. Neither mechanical modification nor additional fiber grating is needed during the sensor fabrication. The results show that the response of magnetic fluid to magnetic field can be used to measure the direction and intensity of magnetic field via whispering gallery modes supported by the U-bent fiber structure with suitable bending radius. The sensitivity of direction is 0.251 nm/°, and the maximum magnetic field intensity sensitivity is 0.517 nm/mT. Besides, the results of this work prove the feasibility for realizing vector magnetic sensors based on other bending structures (such as bending multimode interference, bending SPR structure) in the future.In this paper, we propose and experimentally verify a method for optimizing the fault detection sensitivity of few mode fiber (FMF) link based on high-order spatial mode trend filtering. The employment of high-order mode trend filtering as a signal processing tool identifies meaningful level shifts from FMF optical time-domain reflectometer (FMF-OTDR) profile, which is associated with the problem of the minimization of the intrinsic random noise and modal crosstalk impact on the acquired data. A FMF link fault detection system is built, and the proposed method is utilized to detect the fault loss characteristics of 7.2 km 6-mode fiber with three fusion splice points with different fusion quality, and the detection results of each mode are compared with the results obtained by FMF-OTDR. The experimental results show that our proposed method can effectively improve the low fault detection sensitivity of high-order spatial mode caused by random noise and mode crosstalk.