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To accurately determine the optical axis cut error of a nonlinear uniaxial crystal, a measurement method based on dual-optical path second-harmonic energy (SHE) rocking curve acquisition is presented in, of which the measurement uncertainty can be controlled within 3.20 µrad , 26 times higher than that of a high-precision commercial x-ray diffractometer (XRD). To meet the measurement requirements, a Type I potassium dihydrogen phosphate reference crystal (RC) is first made, and its optical axis cut error is considered as a reference. Then, the optical axis cut error of a measured crystal (MC) with an aperture of 25mm×25mm and a thickness of 10 mm is determined by simultaneously recording the SHE scatter plots of the RC and the MC, where the measurement repeatability of 10 consecutive measurements is only 4.48 µrad and the measurement speed is within 20 s. [https://www.selleckchem.com/products/isoxazole-9-isx-9.html selleck chemicals llc] During data processing, a third-order Fourier polynomial is proposed to fit the scatter plots into smooth curves, of which the regression coefficients are greater than 0.9975. The experimental method not only overcomes the shortcomings that XRDs will introduce scratches and defects to the crystal surface and are unable to measure large-aperture crystals, but can be used to guide the production of precise cutting of a nonlinear uniaxial crystal, thus ensuring the maximum conversion efficiency of a frequency multiplication system.The frequency characteristics of spherical photon density waves excited in media with different degrees of scattering anisotropy are studied. Statistical modeling of the frequency and phase responses of the spatial irradiance of the light field emitted by a point-sized isotropic source were performed employing the Monte Carlo technique. The scattering anisotropy of the medium was determined by the Henyey-Greenstein phase function with different values of the mean scattering cosine. It is shown that the scattering anisotropy factor determines the frequency range, in which the effect of the photon path length distribution on the magnitude of the photon density wave dispersion is maximal. In media with quasi-isotropic scattering, dispersion effects are manifested at lower frequencies as compared to those for anisotropic media. The simulation results are compared with the analytical solution for the asymptotic regime of the light field in an isotropically scattering medium.The security of medical image transmission in telemedicine is very important to patients' privacy and health. A new asymmetric medical image encryption scheme is proposed. The medical image is encrypted by two spiral phase masks (SPM) and the lower-upper decomposition with partial pivoting, where the SPM is generated from the iris, chaotic random phase mask, and amplitude truncated spiral phase transformation. The proposed scheme has the following advantages First, the iris is used for medical image encryption, which improves the security of the encryption scheme. Second, the combination of asymmetric optical encryption and three-dimensional Lorenz chaos improves the key space and solves the linear problem based on double-random phase encoding. Third, compared with other encryption schemes, the proposed scheme has advantages in occlusion attacks, key space, correlation, and information entropy. Numerical simulation and optical results verify the feasibility and robustness of the encryption scheme.We present the characterization of high extinction ratio (ε) square optical pulses using a photon counting technique, as other techniques only offer a limited range of measurement up to 60 dB. High-ε pulses are generated by applying a square pulse modulation on sinusoidally modulated optical signals, then inducing self-phase modulation (SPM) using the nonlinear Kerr effect and extracting an SPM-generated sideband. We measured a 10 ns Kerr-generated optical pulse exhibiting a 120.1 dB extinction ratio, originating from a conventional electro-optic modulator delivering a pulse with a 20-dB extinction ratio, by counting the number of photons at the peak and the pedestal of the generated pulse. These proven high-ε pulses allow for long-range distributed vibration sensing in optical time-domain reflectometry systems and open new horizons in high-Q microring sensors.This paper proposes an unwrapping algorithm based on deep learning for inertial confinement fusion (ICF) target interferograms. With a deep convolutional neural network (CNN), the task of phase unwrapping is transferred into a problem of semantic segmentation. A method for producing the data set for the ICF target measurement system is demonstrated. The noisy wrapped phase is preprocessed using a guided filter. Postprocessing is introduced to refine the final result, ensuring the proposed method can still accurately unwrap the phase even when the segmentation result of the CNN is not perfect. Simulations and actual interferograms show that our method has better accuracy and antinoise ability than some classical unwrapping approaches. In addition, the generalization capability of our method is verified by successfully applying it to an aspheric nonnull test system. By adjusting the data set, the proposed method may be transferred to other systems.We show an in-line digital holographic image reconstruction from subsampled holograms with resolution improvement and lensless magnification with high noise immunity by a compressive sensing approach. Our method treats the sensed field as subsampled, low-pass filtered and projected on a Fresnel-Bluestein base in an inverse problem approach to image reconstruction with controlled lensless magnification. So, we have demonstrated by simulation and experimental results that the approach can reconstruct images with quality even when used in holograms obtained from unusual subsampling schemes.Outgoing Editor-in-Chief Ron Driggers shares his parting thoughts and hopes for the Applied Optics community in the coming year.We experimentally demonstrate Nyquist wavelength-division-multiplexed (WDM) channels with a low signal-to-noise ratio (SNR) difference based on flat electro-optic combs (EOCs), which reduce the interchannel crosstalk penalty in Nyquist-WDM transmission with no guard band. The five Nyquist-WDM channels are generated through the insertion of uniform and coherent lines around each line of the EOCs from a dual-parallel Mach-Zehnder modulator. For the five channels, the normalized root-mean-square error of optical sinc-shaped pulses at a repetition rate of 9 GHz is between 1.23% and 2.04%. The SNRs of the Nyquist signal can be better than 30 dB by using flat EOCs with a narrow linewidth as WDM sources, and the difference in SNR is less than 0.6 dB for the WDM channels. The transmission performance of five Nyquist-WDM channels with no guard band is compared in a 56 km fiber link. The results show that our scheme provides a minimum interchannel sensitivity penalty of 0.7 dB at the forward-error-correction limit. The Nyquist-WDM channels with low SNR difference can effectively improve the communication performance of the Nyquist-WDM system.During welding of glass with ultrafast lasers, an irregular formation of weld seams was prevented by modulation of the average laser power and spatial beam shaping. The formation of individual molten volumes in regular intervals was achieved by means of power modulation, resulting in a predictable and reproducible weld seam with a regular structure. link2 At constant average power, a homogeneous weld seam without a periodic signature was alternatively achieved by means of a shaped beam generating an elongated interaction volume and resulting in a continuous melting of the material. The influence of the two approaches, and their combination on the process dynamics, was analyzed by means of high-speed videos of the plasma emission and of the formation of the seams.The time transformation (TT) technique is used to study the nonlinear pulse reshaping towards triangular pulse (TP) generation by efficiently optimizing the pulse parameters in an erbium-doped chalcogenide fiber amplifier (EDCFA), for the first time, to the best of our knowledge. The effects of input chirp parameter, optical gain, and dipole relaxation time are also depicted in the context of TP generation. The results obtained from the TT approach when compared with that from the nonlinear Schrodinger equation show excellent agreement. The study also reveals that spectral pulse doubling can be achieved at a shorter length when a pre-chirped Gaussian pulse is propagated through the proposed EDCFA.This paper proposes a novel spiral-scanning laser differential confocal measurement method (SSLDCM) for fast and precise measurement of surface topography with microstructures. Spiral plane scanning is used to eliminate frequent acceleration and deceleration problems in traditional raster-scanning differential confocal measurement systems and helps to keep the measuring process efficient and stable. To solve the problem of uneven sampling distribution during spiral scanning, a variable sampling rate method is adopted to distribute the sampling points at equal intervals, which would help to reduce the time of the 3D imaging process. A denoising method based on an adaptive wavelet threshold is proposed to filter the existing noise during the measuring process. An experimental measurement platform based on SSLDCM is constructed, and the axial response curve is tested and analyzed. The linear region range of the experimental platform reaches 13 µm, and the slope is about 164.15 mV/µm. In addition, the measurement results of a silicon wafer specimen by SSLDCM show good consistency with a commercial high-precision microscope, and the largest deviation is less than 2.71%. The SSLDCM has great potential to be used in various noncontact surface measurement applications with high efficiency and accuracy.Robust detection and classification of multimodal self-mixing (SM) signals emanating from the optical feedback-based SM interferometric laser sensor are necessary for accurate retrieval of sensing information. An abrupt shift in the modality of SM signals can occur due to different operating conditions; consequently, an unidentified modality shift can cause severe measurement errors. Therefore, it is necessary to detect and identify the type of multimodality so that relevant adjustments could then be made, either in the SM sensor setup or in the relevant signal processing, to avoid the errors caused by the shift in modality. In this work, SM modality identification and classification techniques based on the machine learning classifier algorithms of linear regression, XGB regressor, and decision tree regressor are proposed. link3 The distinguishing feature values, which are used to train and test the classifiers, are extracted from the given SM signal by applying techniques such as principal component analysis, peak width, and linear discriminant analysis. Proposed methods are tested on an SM signal dataset containing a total of 45 unseen SM signals, acquired experimentally from the SM sensor. The identification and classification accuracy of the three classifiers of linear regression, XGB regressor, and decision tree regressor is 76%, 96%, and 100%, respectively.