Korsgaardblack9302

The simulation results demonstrate that the proposed method provides an average accuracy of 6.1 cm and a maximum positioning error of 17.7 cm in a cubic space with a size of 4 m×4 m×3 m. Compared to the existing least-squares (LS) method that uses total received power, the new method achieves approximately 83% improvement in the mean error of positioning and 81% in root mean square error (RMSE).We theoretically investigate the role of complex dipole phase in the attosecond probing of charge migration. The iodobromoacetylene ion (ICCBr+) is considered as an example, in which one can probe charge migration by accessing both the iodine and bromine ends of the molecule with different spectral windows of an extreme-ultraviolet (XUV) pulse. The analytical expression for transient absorption shows that the site-specific information of charge migration is encoded in the complex phase of cross dipole products for XUV transitions between the I-4d and Br-3d spectral windows. Ab-initio quantum chemistry calculations on ICCBr+ reveal that there is a constant π phase difference between the I-4d and Br-3d transient-absorption spectral windows, irrespective of the fine-structure energy splittings. Transient absorption spectra are simulated with a multistate model including the complex dipole phase, and the results correctly reconstruct the charge-migration dynamics via the quantum beats in the two element spectral windows, exhibiting out-of-phase oscillations.An improved deep neural network incorporating attention mechanism and DSSIM loss function (AM_U_Net) is used to recover input images with speckles transmitted through a multimode fiber (MMF). The network is trained on a relatively small dataset and demonstrates an optimal reconstruction ability and generalization ability. Furthermore, a bimodal fusion method is developed based on S polarization and P polarization speckles, greatly improving the recognition accuracy. These findings prove that AM_U_Net has remarkable capabilities for information recovery and transfer learning and good tolerance and robustness under different MMF transmission conditions, indicating its significant application potential in medical imaging and secure communication.We propose a high-precision micro-displacement measurement method based on alternately oscillating optoelectronic oscillators (OEOs). This method uses a reference loop to compensate for the change in the measuring loop length except for the displacement to be measured. Therefore, self-calibration is realized without using a phase-locked loop to control the loop length, greatly simplifying the system. The measurement range is 20 mm, and the measurement precision is less then 300 nm, which is limited by the incomplete consistency between the reference and the measuring loops, with the exception of the displacement to be measured and environmental disturbances resulting from the spatial optical path.The fiber-coupling efficiency of signal beams is crucial in free space optical (FSO) communications. Herein, we derived an analytical expression for the fiber-coupling efficiency of partially coherent flat-topped beams propagating through atmospheric turbulence based on the cross-spectral density function. Our numerical calculation results showed that the fiber-coupling efficiency of partially coherent flat-topped beams in a turbulent atmosphere could be enhanced by increasing the beam order. Under the same conditions, the fiber-coupling efficiency of the high-order partially coherent flat-topped beams was larger than those connected to the Gaussian and Gaussian Schell-model (GSM) beams. PF-04965842 Our results will improve the quality of partially coherent beams used in FSO communications.In this paper, the Karhunen-Loeve transform (KLT) and wavelength domain interferometric spectral singular value decomposition (SVD) are used for the first time to demodulate the pressure of an optical fiber Fabry-Perot (F-P) micro-pressure sensor, and the feasibility of the proposed method is demonstrated experimentally. The eigenvalue decomposition of the dominant frequency part of the beam-domain interferometric spectrum after the fast Fourier transform (FFT) is performed using KLT, and the singular value decomposition of the wavelength domain interferometric spectrum is additionally performed using SVD. Both methods use high-order eigenvalues as a new metric and then derive the relation between the new metric and the reference pressure. The two demodulation methods are experimentally compared, and we used an optical fiber F-P pressure sensor with unknown structure and material for pressure measurements. Even though the interferometric spectral signal is acquired using a coarse spectrometer (2.5 nm wavelength resolution), one can still achieve high demodulation accuracy with both algorithms. However, the SVD demodulation accuracy decreases significantly after reducing the spectral data points in the wavelength domain from 1566 to 783. KLT still has high demodulation accuracy and linearity after spectral data points are reduced from 1024 to 256 in the wavenumber domain. The satisfactory linearity of the measured pressure versus reference pressure and low reading errors validate the feasibility of the proposed demodulation algorithm.We investigate gentle front side textures for perovskite/silicon tandem solar cells. These textures enhance the absorption of sunlight, yet are sufficiently gentle to allow deposition of an efficient perovskite top cell. We present a tandem solar cell with such gentle texture, fabricated by Kaneka corporation, with an efficiency as high as 28.6%. We perform an extensive ray-optics study, exploring non-conformal textures at the front and rear side of the perovskite layer. Our results reveal that a gentle texture with steepness of only 23° can be more optically efficient than conventional textures with more than double that steepness. We also show that the observed anti-reflective effect of such gentle textures is not based a double bounce, but on light trapping by total internal reflection. As a result, the optical effects of the encapsulation layers play an important role, and have to be accounted for when evaluating the texture design for perovskite/silicon tandems.Hyperbolic materials have wide application prospects, such as all-angle negative refraction, sub-diffraction imaging and nano-sensing, owning to the unusual electromagnetic response characteristics. Compared with artificial hyperbolic metamaterials, natural hyperbolic materials have many advantages. Anisotropic two-dimensional (2D) materials show great potential in the field of optoelectronics due to the intrinsic in-plane anisotropy. Here, the electronic and optical properties of two hyperbolic 2D materials, monolayer CuB6 and CuB3, are investigated using first-principles calculations. They are predicted to have multiple broadband hyperbolic windows with low loss and highly-anisotropic plasmon excitation from infrared to ultraviolet regions. Remarkably, plasmon propagation along the x-direction is almost forbidden in CuB3 monolayer. The hyperbolic windows and plasmonic properties of these 2D copper borides can be effectively regulated by electron (or hole) doping, which offers a promising strategy for tuning the optical properties of the materials.Jerk is directly related to a physical mutation process of structural damage and human comfort. A fiber optic jerk sensor (FOJS) based on a fiber optic differentiating Mach-Zehnder interferometer is proposed. It can directly measure jerk by demodulating the phase of interference light, which avoids the high-frequency noise interference caused by differentiating the acceleration. The sensing theory and sensor design are given in detail. The experimental and theoretical results agree, demonstrating that the FOJS has a high sensitivity, an ultralow phase noise floor, a wide measuring range, and good linearity. The impact test shows that the FOJS can directly measure jerk and has good consistency with a standard piezoelectric accelerometer. The FOJS has potential applications in earthquake engineering, comfort evaluations, and railway design. This is the first time that directly measuring jerk with an optical sensor is reported.Orbital angular momentum (OAM) mode multiplexing provides a new strategy for reconstructing multiple holograms, which is compatible with other physical dimensions involving wavelength and polarization to enlarge information capacity. Conventional OAM multiplexing holography usually relies on the independence of physical dimensions, and the deep holography involving spatial depth is always limited for the lack of spatiotemporal evolution modulation technologies. Herein, we introduce a depth-controllable imaging technology in OAM deep multiplexing holography via designing a prototype of five-layer optical diffractive neural network (ODNN). Since the optical propagation with dimensional-independent spatiotemporal evolution offers a unique linear modulation to light, it is possible to combine OAM modes with spatial depths to realize OAM deep multiplexing holography. Exploiting the multi-plane light conversion and in-situ optical propagation principles, we simultaneously modulate both the OAM mode and spatial depth of incident light via unitary transformation and linear modulations, where OAM modes are encoded independently for conversions among holograms. Results show that the ODNN realized light field conversion and evolution of five multiplexed OAM modes in deep multiplexing holography, where the mean square error and structural similarity index measure are 0.03 and 86%, respectively. Our demonstration explores a depth-controllable spatiotemporal evolution technology in OAM deep multiplexing holography, which is expected to promote the development of OAM mode-based optical holography and storage.A suitable scheme to continuously create inversion on an optical clock transition with negligible perturbation is a key missing ingredient required to build an active optical atomic clock. Repumping of the atoms on the narrow transition typically needs several pump lasers in a multi step process involving several auxiliary levels. In general this creates large effective level shifts and a line broadening, strongly limiting clock accuracy. Here we present an extensive theoretical study for a realistic multi-level implementation in search of parameter regimes where a sufficient inversion can be achieved with minimal perturbations. Fortunately we are able to identify a useful operating regime, where the frequency shifts remain small and controllable, only weakly perturbing the clock transition for useful pumping rates. For practical estimates of the corresponding clock performance, we introduce a straightforward mapping of the multilevel pump scheme to an effective energy shift and broadening of parameters for the reduced two-level laser model system. This allows us to evaluate the resulting laser power and spectrum using well-known methods.Multi-classification using a convolutional neural network (CNN) is proposed as a denoising method for coherent Doppler wind lidar (CDWL) data. The method is intended to enhance the usable range of a CDWL beyond the atmospheric boundary layer (ABL). The method is implemented and tested in an all-fiber pulsed CWDL system operating at 1550 nm wavelength with 20 kHz repetition rate, 300 ns pulse length and 180 µJ of laser energy. Real-time pre-processing using a field programmable gate array (FPGA) is implemented producing averaged lidar spectrograms. Real-world measurement data is labeled using conventional frequency estimators and mixed with simulated spectrograms for training of the CNN. First results of this methods show that the CNN can outperform conventional frequency estimations substantially in terms of maximum range and delivers reasonable output in very low signal-to-noise (SNR) situations while still delivering accurate results in the high-SNR regime. Comparing the CNN output with radiosonde data shows the feasibility of the proposed method.